IDEAS home Printed from https://ideas.repec.org/r/bla/jorssb/v72y2010i3p269-342.html

Particle Markov chain Monte Carlo methods

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Andrew Hoegh & Frank T. Manen & Mark Haroldson, 2021. "Agent-Based Models for Collective Animal Movement: Proximity-Induced State Switching," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(4), pages 560-579, December.
  2. Wolf, Elias, 2022. "Estimating growth at risk with skewed stochastic volatility models," Discussion Papers 2022/2, Free University Berlin, School of Business & Economics.
  3. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
  4. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
  5. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, November.
  6. Herbst, Edward & Schorfheide, Frank, 2019. "Tempered particle filtering," Journal of Econometrics, Elsevier, vol. 210(1), pages 26-44.
  7. Ajay Jasra & Kody Law & Carina Suciu, 2020. "Advanced Multilevel Monte Carlo Methods," International Statistical Review, International Statistical Institute, vol. 88(3), pages 548-579, December.
  8. Jin, Guang & Matthews, David E. & Zhou, Zhongbao, 2013. "A Bayesian framework for on-line degradation assessment and residual life prediction of secondary batteries inspacecraft," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 7-20.
  9. Kouritzin, Michael A., 2017. "Residual and stratified branching particle filters," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 145-165.
  10. Henri Pesonen & Umberto Simola & Alvaro Köhn‐Luque & Henri Vuollekoski & Xiaoran Lai & Arnoldo Frigessi & Samuel Kaski & David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Jukka Corander, 2023. "ABC of the future," International Statistical Review, International Statistical Institute, vol. 91(2), pages 243-268, August.
  11. Radu Herbei & L. Mark Berliner, 2014. "Estimating Ocean Circulation: An MCMC Approach With Approximated Likelihoods via the Bernoulli Factory," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 944-954, September.
  12. Nonejad, Nima, 2014. "Particle Gibbs with Ancestor Sampling Methods for Unobserved Component Time Series Models with Heavy Tails, Serial Dependence and Structural Breaks," MPRA Paper 55664, University Library of Munich, Germany.
  13. Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023. "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers 2308.00913, arXiv.org, revised Aug 2025.
  14. Mengheng Li & Marcel Scharth, 2022. "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 285-301, January.
  15. Salima El Kolei, 2013. "Parametric estimation of hidden stochastic model by contrast minimization and deconvolution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(8), pages 1031-1081, November.
  16. Piergiorgio Alessandri & Haroon Mumtaz, 2021. "The Macroeconomic Cost of Climate Volatility," Working Papers 928, Queen Mary University of London, School of Economics and Finance.
  17. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
  18. Ignatieva, Katja & Wong, Patrick, 2024. "Empirical analysis of crude oil dynamics using affine vs. non-affine jump-diffusion models," Journal of Empirical Finance, Elsevier, vol. 78(C).
  19. Huang, Jing-Zhi & Ni, Jun & Xu, Li, 2022. "Leverage effect in cryptocurrency markets," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
  20. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
  21. Cozzini, Alberto & Jasra, Ajay & Montana, Giovanni & Persing, Adam, 2014. "A Bayesian mixture of lasso regressions with t-errors," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 84-97.
  22. Ioannis Andrianakis & Ian R Vernon & Nicky McCreesh & Trevelyan J McKinley & Jeremy E Oakley & Rebecca N Nsubuga & Michael Goldstein & Richard G White, 2015. "Bayesian History Matching of Complex Infectious Disease Models Using Emulation: A Tutorial and a Case Study on HIV in Uganda," PLOS Computational Biology, Public Library of Science, vol. 11(1), pages 1-18, January.
  23. Douc, Randal & Olsson, Jimmy & Roueff, François, 2020. "Posterior consistency for partially observed Markov models," Stochastic Processes and their Applications, Elsevier, vol. 130(2), pages 733-759.
  24. Patrick Leung & Catherine S. Forbes & Gael M Martin & Brendan McCabe, 2019. "Forecasting Observables with Particle Filters: Any Filter Will Do!," Monash Econometrics and Business Statistics Working Papers 22/19, Monash University, Department of Econometrics and Business Statistics.
  25. Espen Bernton & Pierre E. Jacob & Mathieu Gerber & Christian P. Robert, 2019. "Approximate Bayesian computation with the Wasserstein distance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 235-269, April.
  26. Nicolas Chopin & Sumeetpal S. Singh, 2013. "On the Particle Gibbs Sampler," Working Papers 2013-41, Center for Research in Economics and Statistics.
  27. Ha Nguyen, 2023. "Particle MCMC in forecasting frailty correlated default models with expert opinion," Papers 2304.11586, arXiv.org, revised Aug 2023.
  28. Martin Andreasen & Andrew Meldrum, 2013. "Likelihood inference in non-linear term structure models: the importance of the lower bound," Bank of England working papers 481, Bank of England.
  29. William W. Chow, 2025. "Inflation cost of strategic goods export restriction: evidence from dynamic spatial panel data model," International Economics and Economic Policy, Springer, vol. 22(4), pages 1-25, October.
  30. Johan Dahlin & Fredrik Lindsten & Thomas B. Schon, 2015. "Quasi-Newton particle Metropolis-Hastings," Papers 1502.03656, arXiv.org, revised Sep 2015.
  31. Lux, Thomas, 2020. "Bayesian estimation of agent-based models via adaptive particle Markov chain Monte Carlo," Economics Working Papers 2020-01, Christian-Albrechts-University of Kiel, Department of Economics.
  32. Golightly Andrew & Wilkinson Darren J., 2015. "Bayesian inference for Markov jump processes with informative observations," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(2), pages 169-188, April.
  33. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
  34. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
  35. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
  36. Phoebe Koundouri & Nikolaos Englezos & Xanthi Kartala & Mike Tsionas, 2019. "A Decision-Analytic Framework to explore the water-energy-food nexus in complex and transboundary water resources systems, with Climate Change Uncertainty," DEOS Working Papers 1907, Athens University of Economics and Business.
  37. Gareth W. Peters & Mark Briers & Pavel V. Shevchenko & Arnaud Doucet, 2011. "Calibration and filtering for multi factor commodity models with seasonality: incorporating panel data from futures contracts," Papers 1105.5850, arXiv.org.
  38. Chau, Thi Tuyet Trang & Ailliot, Pierre & Monbet, Valérie, 2021. "An algorithm for non-parametric estimation in state–space models," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  39. Fasolo, Angelo Marsiglia, 2019. "Monetary policy volatility shocks in Brazil," Economic Modelling, Elsevier, vol. 81(C), pages 348-360.
  40. Garbuno-Inigo, A. & DiazDelaO, F.A. & Zuev, K.M., 2016. "Gaussian process hyper-parameter estimation using Parallel Asymptotically Independent Markov Sampling," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 367-383.
  41. Mumtaz, Haroon & Theodoridis, Konstantinos, 2020. "Dynamic effects of monetary policy shocks on macroeconomic volatility," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 262-282.
  42. Stamatina Lamprinakou & Axel Gandy & Emma McCoy, 2023. "Using a latent Hawkes process for epidemiological modelling," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-27, March.
  43. Virbickaitė, Audronė & Lopes, Hedibert F. & Zaharieva, Martina Danielova, 2025. "Multivariate dynamic mixed-frequency density pooling for financial forecasting," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1184-1198.
  44. Laura Liu & Mikkel Plagborg‐Møller, 2023. "Full‐information estimation of heterogeneous agent models using macro and micro data," Quantitative Economics, Econometric Society, vol. 14(1), pages 1-35, January.
  45. Iiboshi, Hirokuni & Shintani, Mototsugu, 2016. "Zero interest rate policy and asymmetric price adjustment in Japan: an empirical analysis of a nonlinear DSGE model," MPRA Paper 93868, University Library of Munich, Germany.
  46. Chris Sherlock, 2021. "Direct statistical inference for finite Markov jump processes via the matrix exponential," Computational Statistics, Springer, vol. 36(4), pages 2863-2887, December.
  47. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2012. "Bayesian Estimation of a Dynamic Game with Endogenous, Partially Observed, Serially Correlated State," Working Papers 12-01, Duke University, Department of Economics.
  48. Ioannis Bournakis & Mike Tsionas, 2024. "A Non‐parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 641-671, June.
  49. Roberto León-González, 2019. "Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 899-920, September.
  50. Papp, Tamás K. & Reiter, Michael, 2020. "Estimating linearized heterogeneous agent models using panel data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
  51. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
  52. Ron Gallant & Raffaella Giacomini & Giuseppe Ragusa, 2013. "Generalized method of moments with latent variables," CeMMAP working papers CWP50/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  53. Brix, Anne Floor & Lunde, Asger & Wei, Wei, 2018. "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method," Energy Economics, Elsevier, vol. 72(C), pages 560-582.
  54. Aruoba, S. Borağan & Bocola, Luigi & Schorfheide, Frank, 2017. "Assessing DSGE model nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 83(C), pages 34-54.
  55. Siming Liang & Hui Sun & Richard Archibald & Feng Bao, 2024. "Convergence Analysis for an Online Data-Driven Feedback Control Algorithm," Mathematics, MDPI, vol. 12(16), pages 1-28, August.
  56. repec:rim:rimwps:18-38 is not listed on IDEAS
  57. Picchini, Umberto & Anderson, Rachele, 2017. "Approximate maximum likelihood estimation using data-cloning ABC," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 166-183.
  58. Christophe Chesneau & Salima El Kolei & Fabien Navarro, 2017. "Parametric estimation of hidden Markov models by least squares type estimation and deconvolution," Working Papers 2017-66, Center for Research in Economics and Statistics.
  59. Chen, Han & Fei, Yijie & Yu, Jun, 2025. "Multivariate stochastic volatility models based on generalized Fisher transformation," Journal of Econometrics, Elsevier, vol. 251(C).
  60. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  61. Guay, François & Schwenkler, Gustavo, 2021. "Efficient estimation and filtering for multivariate jump–diffusions," Journal of Econometrics, Elsevier, vol. 223(1), pages 251-275.
  62. S Borağan Aruoba & Pablo Cuba-Borda & Frank Schorfheide, 2018. "Macroeconomic Dynamics Near the ZLB: A Tale of Two Countries," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(1), pages 87-118.
  63. Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1073-1085, November.
  64. Sabiwalsky, Ralf, 2012. "Does Basel II pillar 3 risk exposure data help to identify risky banks?," SFB 649 Discussion Papers 2012-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  65. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
  66. Teresa K Yamana & Sasikiran Kandula & Jeffrey Shaman, 2017. "Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-17, November.
  67. Jue Tao Lim & Yiting Han & Borame Sue Lee Dickens & Lee Ching Ng & Alex R Cook, 2020. "Time varying methods to infer extremes in dengue transmission dynamics," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-19, October.
  68. Isambi Mbalawata & Simo Särkkä & Heikki Haario, 2013. "Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering," Computational Statistics, Springer, vol. 28(3), pages 1195-1223, June.
  69. Johan Dahlin & Mattias Villani & Thomas B. Schon, 2015. "Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods," Papers 1506.06975, arXiv.org, revised Jun 2017.
  70. István Barra & Lennart Hoogerheide & Siem Jan Koopman & André Lucas, 2017. "Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 1003-1026, August.
  71. Yu Mu & Robert J. Frey, 2025. "Particle Filtering Estimation of Regime Switching Factor Model and Its Application in Statistical Arbitrage Strategy," JRFM, MDPI, vol. 18(10), pages 1-22, October.
  72. Huan, Yue & Wang, Guoqiang & Lin, Hai Xiang, 2026. "Sequential hierarchical Bayesian model and particle filter estimation with two-step RJMCMC resampling," Computational Statistics & Data Analysis, Elsevier, vol. 216(C).
  73. Haroon Mumtaz & Alberto Musso, 2021. "The Evolving Impact of Global, Region-Specific, and Country-Specific Uncertainty," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 466-481, March.
  74. Yuta Kurose & Yasuhiro Omori, "undated". "Multiple-lock Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1075, CIRJE, Faculty of Economics, University of Tokyo.
  75. Danilo Cascaldi-Garcia, 2017. "Amplification effects of news shocks through uncertainty," 2017 Papers pca1251, Job Market Papers.
  76. Nguyen, Dao, 2016. "Another look at Bayes map iterated filtering," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 32-36.
  77. Christophe Chesneau & Salima El Kolei & Fabien Navarro, 2022. "Parametric estimation of hidden Markov models by least squares type estimation and deconvolution," Statistical Papers, Springer, vol. 63(5), pages 1615-1648, October.
  78. Delis, Manthos D. & Iosifidi, Maria & Kazakis, Pantelis & Ongena, Steven & Tsionas, Mike G., 2022. "Management practices and M&A success," Journal of Banking & Finance, Elsevier, vol. 134(C).
  79. Chen Gong & David S. Stoffer, 2021. "A Note on Efficient Fitting of Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 186-200, March.
  80. repec:rau:journl:v:10:y:2016:i:2:p:435-447 is not listed on IDEAS
  81. Eugenia Koblents & Inés P. Mariño & Joaquín Míguez, 2019. "Bayesian Computation Methods for Inference in Stochastic Kinetic Models," Complexity, Hindawi, vol. 2019, pages 1-15, January.
  82. Nguyen Ba Trung, 2022. "Output fluctuations and portfolio flows to emerging economies: The role of monetary uncertainty," International Finance, Wiley Blackwell, vol. 25(3), pages 285-295, December.
  83. Hubin, Aliaksandr & Storvik, Geir, 2018. "Mode jumping MCMC for Bayesian variable selection in GLMM," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 281-297.
  84. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
  85. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.
  86. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
  87. Li, Yanxin & Walker, Stephen G., 2023. "A latent slice sampling algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
  88. Arnaud Doucet & Neil Shephard, 2012. "Robust inference on parameters via particle filters and sandwich covariance matrices," Economics Papers 2012-W05, Economics Group, Nuffield College, University of Oxford.
  89. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," LIDAM Discussion Papers CORE 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  90. Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
  91. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Bayesian analysis of chaos: The joint return-volatility dynamical system," MPRA Paper 80632, University Library of Munich, Germany.
  92. Svetoslav Kostov & Nick Whiteley, 2017. "An Algorithm for Approximating the Second Moment of the Normalizing Constant Estimate from a Particle Filter," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 799-818, September.
  93. Fabian Goessling, 2018. "Randomized Quasi Sequential Markov Chain Monte Carlo²," CQE Working Papers 7018, Center for Quantitative Economics (CQE), University of Muenster.
  94. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
  95. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
  96. Tore Selland Kleppe, 2016. "Adaptive Step Size Selection for Hessian-Based Manifold Langevin Samplers," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 788-805, September.
  97. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
  98. Delis, Manthos D. & Kazakis, Pantelis & Zopounidis, Constantin, 2023. "Management and takeover decisions," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1256-1268.
  99. Persing, Adam & Jasra, Ajay, 2013. "Likelihood computation for hidden Markov models via generalized two-filter smoothing," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1433-1442.
  100. Th I Götz & G Lahmer & V Strnad & Ch Bert & B Hensel & A M Tomé & E W Lang, 2017. "A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-31, September.
  101. Nonejad, Nima, 2015. "Flexible model comparison of unobserved components models using particle Gibbs with ancestor sampling," Economics Letters, Elsevier, vol. 133(C), pages 35-39.
  102. S. Bogan Aruoba & Pablo Cuba-Borda & Kenji Higa-Flores & Frank Schorfheide & Sergio Villalvazo, 2021. "Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 41, pages 96-120, July.
  103. Del Negro, Marco & Hasegawa, Raiden B. & Schorfheide, Frank, 2016. "Dynamic prediction pools: An investigation of financial frictions and forecasting performance," Journal of Econometrics, Elsevier, vol. 192(2), pages 391-405.
  104. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2017. "Cohort effects in mortality modelling: a Bayesian state-space approach," Papers 1703.08282, arXiv.org.
  105. Christopher Gust & Edward Herbst & David López-Salido & Matthew E. Smith, 2017. "The Empirical Implications of the Interest-Rate Lower Bound," American Economic Review, American Economic Association, vol. 107(7), pages 1971-2006, July.
  106. Skvortsov, Alex & Ristic, Branko & Kamenev, Alex, 2018. "Predicting population extinction from early observations of the Lotka–Volterra system," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 371-379.
  107. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
  108. Laura Liu & Mikkel Plagborg-M{o}ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," Papers 2101.04771, arXiv.org, revised Jun 2022.
  109. Laurent-Emmanuel Calvet & Veronika Czellar, 2011. "State-Observation Sampling and the Econometrics of Learning Models," Working Papers hal-00625500, HAL.
  110. Burkhart, Michael C., 2019. "A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding," Thesis Commons 4j3fu, Center for Open Science.
  111. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
  112. Lux, Thomas, 2018. "Estimation of agent-based models using sequential Monte Carlo methods," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 391-408.
  113. James M. Nason & Gregor W. Smith, 2021. "Measuring the slowly evolving trend in US inflation with professional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.
  114. Haroon Mumtaz & Katerina Petrova, 2023. "Changing Impact of Shocks: A Time‐Varying Proxy SVAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(2-3), pages 635-654, March.
  115. Wei Wei & Asger Lunde, 2023. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1647-1679.
  116. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
  117. Alzahrani, Naif & Neal, Peter & Spencer, Simon E.F. & McKinley, Trevelyan J. & Touloupou, Panayiota, 2018. "Model selection for time series of count data," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 33-44.
  118. Tim Hagenhoff & Joep Lustenhouwer & Mike Tsionas, 2025. "The Rationality Bias," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 57(2-3), pages 515-547, March.
  119. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
  120. Arnaud Dufays, 2016. "Evolutionary Sequential Monte Carlo Samplers for Change-Point Models," Econometrics, MDPI, vol. 4(1), pages 1-33, March.
  121. Yuan Shen & Dan Cornford & Manfred Opper & Cedric Archambeau, 2012. "Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions," Computational Statistics, Springer, vol. 27(1), pages 149-176, March.
  122. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
  123. Haroon Mumtaz, 2020. "A Generalised Stochastic Volatility in Mean VAR. An Updated Algorithm," Working Papers 908, Queen Mary University of London, School of Economics and Finance.
  124. Asger Lunde & Anne Floor Brix & Wei Wei, 2015. "A Generalized Schwartz Model for Energy Spot Prices - Estimation using a Particle MCMC Method," CREATES Research Papers 2015-46, Department of Economics and Business Economics, Aarhus University.
  125. repec:bla:istatr:v:83:y:2015:i:3:p:405-435 is not listed on IDEAS
  126. Jonathan U Harrison & Ruth E Baker, 2020. "An automatic adaptive method to combine summary statistics in approximate Bayesian computation," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-21, August.
  127. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
  128. Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized Neural Networks for Agent-Based Model Forecasting," Bank of Russia Working Paper Series wps115, Bank of Russia.
  129. Wan Yang & Alicia Karspeck & Jeffrey Shaman, 2014. "Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-15, April.
  130. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
  131. Del Moral, Pierre & Jasra, Ajay, 2018. "A sharp first order analysis of Feynman–Kac particle models, Part II: Particle Gibbs samplers," Stochastic Processes and their Applications, Elsevier, vol. 128(1), pages 354-371.
  132. Fileccia, Gaetano & Sgarra, Carlo, 2018. "A particle filtering approach to oil futures price calibration and forecasting," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 21-34.
  133. Elmar Mertens & James M. Nason, 2020. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
  134. repec:rau:journl:v:10:y:2015:i:2:p:384-394 is not listed on IDEAS
  135. Christopher Wikle & Mevin Hooten, 2010. "A general science-based framework for dynamical spatio-temporal models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 417-451, November.
  136. Dupret, Jean-Loup & Hainaut, Donatien, 2022. "A subdiffusive stochastic volatility jump model," LIDAM Discussion Papers ISBA 2022001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  137. Narci, Romain & Delattre, Maud & Larédo, Catherine & Vergu, Elisabeta, 2021. "Inference for partially observed epidemic dynamics guided by Kalman filtering techniques," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
  138. Manthos D. Delis & Pantelis Kazakis & Constantin Zopounidis, 2021. "Management Practices and Takeover Decisions," Working Papers 2021_10, Business School - Economics, University of Glasgow.
  139. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
  140. Sebastian Funk & Anton Camacho & Adam J Kucharski & Rachel Lowe & Rosalind M Eggo & W John Edmunds, 2019. "Assessing the performance of real-time epidemic forecasts: A case study of Ebola in the Western Area region of Sierra Leone, 2014-15," PLOS Computational Biology, Public Library of Science, vol. 15(2), pages 1-17, February.
  141. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
  142. Jaeho Kim & Sora Chon, 2022. "Bayesian estimation of the long-run trend of the US economy," Empirical Economics, Springer, vol. 62(2), pages 461-485, February.
  143. Matti Vihola & Jouni Helske & Jordan Franks, 2020. "Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1339-1376, December.
  144. Turnbull, Kathryn & Nemeth, Christopher & Nunes, Matthew & McCormick, Tyler, 2023. "Sequential estimation of temporally evolving latent space network models," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
  145. Rimstad, Kjartan & Omre, Henning, 2013. "Approximate posterior distributions for convolutional two-level hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 187-200.
  146. Dima, Bogdan & Dima, Ştefana Maria & Ioan, Roxana, 2025. "The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 98(C).
  147. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2013. "Indirect Inference in fractional short-term interest rate diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 109-126.
  148. Haroon Mumtaz, 2018. "A generalised stochastic volatility in mean VAR," Working Papers 855, Queen Mary University of London, School of Economics and Finance.
  149. Ignatieva, Katja & Wong, Patrick, 2022. "Modelling high frequency crude oil dynamics using affine and non-affine jump–diffusion models," Energy Economics, Elsevier, vol. 108(C).
  150. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
  151. Nathan Cunningham & Jim E. Griffin & David L. Wild, 2020. "ParticleMDI: particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 463-484, June.
  152. Thomas Rawson & Christian Morgenstern & Edward S. Knock & Joseph Hicks & Anh Pham & Guillaume Morel & Aurelio Cabezas Murillo & Michael W. Sanderson & Giovanni Forchini & Richard FitzJohn & Katharina , 2025. "A mathematical model of H5N1 influenza transmission in US dairy cattle," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
  153. Baştürk, N. & Borowska, A. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2019. "Forecast density combinations of dynamic models and data driven portfolio strategies," Journal of Econometrics, Elsevier, vol. 210(1), pages 170-186.
  154. Franks, Jordan & Vihola, Matti, 2020. "Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 6157-6183.
  155. repec:dau:papers:123456789/11429 is not listed on IDEAS
  156. Drew D. Creal & Jing Cynthia Wu, 2020. "Bond risk premia in consumption‐based models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1461-1484, November.
  157. Wolf, Elias, 2023. "Estimating Growth at Risk with Skewed Stochastic Volatility Models," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277696, Verein für Socialpolitik / German Economic Association.
  158. Weiwei Zhang & Shiyong Liu & Nathaniel Osgood & Hongli Zhu & Ying Qian & Peng Jia, 2023. "Using simulation modelling and systems science to help contain COVID‐19: A systematic review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(1), pages 207-234, January.
  159. Lau, F. Din-Houn & Gandy, Axel, 2014. "RMCMC: A system for updating Bayesian models," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 99-110.
  160. Haroon Mumtaz & Konstantinos Theodoridis, 2016. "Volatility Co-movement and the Great Moderation. An Empirical Analysis," Working Papers 804, Queen Mary University of London, School of Economics and Finance.
  161. Hall, Jamie, 2012. "Consumption dynamics in general equilibrium," MPRA Paper 43933, University Library of Munich, Germany.
  162. Nonejad, Nima, 2014. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," MPRA Paper 55662, University Library of Munich, Germany.
  163. Marco J Morelli & Gaël Thébaud & Joël Chadœuf & Donald P King & Daniel T Haydon & Samuel Soubeyrand, 2012. "A Bayesian Inference Framework to Reconstruct Transmission Trees Using Epidemiological and Genetic Data," PLOS Computational Biology, Public Library of Science, vol. 8(11), pages 1-14, November.
  164. Wang, Nianling & Lou, Zhusheng, 2023. "Sequential Bayesian analysis for semiparametric stochastic volatility model with applications," Economic Modelling, Elsevier, vol. 123(C).
  165. Markéta Zikmundová & Kateřina Staňková Helisová & Viktor Beneš, 2014. "On the Use of Particle Markov Chain Monte Carlo in Parameter Estimation of Space-Time Interacting Discs," Methodology and Computing in Applied Probability, Springer, vol. 16(2), pages 451-463, June.
  166. Paul Fearnhead & Omiros Papaspiliopoulos & Gareth O. Roberts & Andrew Stuart, 2010. "Random‐weight particle filtering of continuous time processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(4), pages 497-512, September.
  167. Brignone, Riccardo & Gonzato, Luca & Lütkebohmert, Eva, 2023. "Efficient Quasi-Bayesian Estimation of Affine Option Pricing Models Using Risk-Neutral Cumulants," Journal of Banking & Finance, Elsevier, vol. 148(C).
  168. N. Englezos & X. Kartala & P. Koundouri & M. Tsionas & A. Alamanos, 2023. "A Novel HydroEconomic - Econometric Approach for Integrated Transboundary Water Management Under Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 975-1030, April.
  169. Bastian Gribisch, 2016. "Multivariate Wishart stochastic volatility and changes in regime," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 443-473, October.
  170. Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Productivity and Performance: A GMM approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 331-344, April.
  171. Beskos, Alexandros & Kalogeropoulos, Konstantinos & Pazos, Erik, 2013. "Advanced MCMC methods for sampling on diffusion pathspace," Stochastic Processes and their Applications, Elsevier, vol. 123(4), pages 1415-1453.
  172. Sun, Libo & Lee, Chihoon & Hoeting, Jennifer A., 2015. "A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 54-67.
  173. Cheng, Jing & Chan, Ngai Hang, 2019. "Efficient inference for nonlinear state space models: An automatic sample size selection rule," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 143-154.
  174. Naoki Awaya & Yasuhiro Omori, 2021. "Particle Rolling MCMC with Double-Block Sampling ," CIRJE F-Series CIRJE-F-1175, CIRJE, Faculty of Economics, University of Tokyo.
  175. Pratiti Chatterjee & David Gunawan & Robert Kohn, 2020. "The Interaction Between Credit Constraints and Uncertainty Shocks," Papers 2004.14719, arXiv.org.
  176. Arellano, Manuel & Blundell, Richard & Bonhomme, Stéphane & Light, Jack, 2024. "Heterogeneity of consumption responses to income shocks in the presence of nonlinear persistence," Journal of Econometrics, Elsevier, vol. 240(2).
  177. Brown, Suzie & Jenkins, Paul A. & Johansen, Adam M. & Koskela, Jere, 2023. "Weak convergence of non-neutral genealogies to Kingman’s coalescent," Stochastic Processes and their Applications, Elsevier, vol. 162(C), pages 76-105.
  178. Gareth William Peters & Mark Briers & Pavel Shevchenko & Arnaud Doucet, 2013. "Calibration and Filtering for Multi Factor Commodity Models with Seasonality: Incorporating Panel Data from Futures Contracts," Methodology and Computing in Applied Probability, Springer, vol. 15(4), pages 841-874, December.
  179. Szczepocki Piotr, 2020. "Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process," Statistics in Transition New Series, Statistics Poland, vol. 21(2), pages 173-187, June.
  180. Prado, Raquel, 2013. "Sequential estimation of mixtures of structured autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 58-70.
  181. Heine, Kari & Whiteley, Nick, 2017. "Fluctuations, stability and instability of a distributed particle filter with local exchange," Stochastic Processes and their Applications, Elsevier, vol. 127(8), pages 2508-2541.
  182. Sanha Noh, 2020. "Posterior Inference on Parameters in a Nonlinear DSGE Model via Gaussian-Based Filters," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 795-841, December.
  183. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
  184. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
  185. Neil Shephard & Thomas Flury, 2009. "Learning and filtering via simulation: smoothly jittered particle filters," Economics Series Working Papers 469, University of Oxford, Department of Economics.
  186. Duan, Jin-Chuan & Fulop, Andras & Hsieh, Yu-Wei, 2020. "Data-cloning SMC2: A global optimizer for maximum likelihood estimation of latent variable models," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
  187. I. Andrianakis & I. Vernon & N. McCreesh & T. J. McKinley & J. E. Oakley & R. N. Nsubuga & M. Goldstein & R. G. White, 2017. "History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 717-740, August.
  188. Hall, Jamie & Pitt, Michael K. & Kohn, Robert, 2014. "Bayesian inference for nonlinear structural time series models," Journal of Econometrics, Elsevier, vol. 179(2), pages 99-111.
  189. Alaa Jamal & Raphael Linker, 2020. "Genetic Operator-Based Particle Filter Combined with Markov Chain Monte Carlo for Data Assimilation in a Crop Growth Model," Agriculture, MDPI, vol. 10(12), pages 1-22, December.
  190. Feng, Jingxue & Wang, Liangliang, 2024. "A switching state-space transmission model for tracking epidemics and assessing interventions," Computational Statistics & Data Analysis, Elsevier, vol. 197(C).
  191. Adam Persin & Ajay Jasr, 2016. "Twisting the Alive Particle Filter," Methodology and Computing in Applied Probability, Springer, vol. 18(2), pages 335-358, June.
  192. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
  193. Donnat, Claire & Klopp, Olga & Verzelen, Nicolas, 2026. "Denoising over networks with applications to partially observed epidemics," Computational Statistics & Data Analysis, Elsevier, vol. 215(C).
  194. Jonathan Fintzi & Jon Wakefield & Vladimir N. Minin, 2022. "A linear noise approximation for stochastic epidemic models fit to partially observed incidence counts," Biometrics, The International Biometric Society, vol. 78(4), pages 1530-1541, December.
  195. N. Chopin & P. E. Jacob & O. Papaspiliopoulos, 2013. "SMC-super-2: an efficient algorithm for sequential analysis of state space models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 397-426, June.
  196. Giorgos Sermaidis & Omiros Papaspiliopoulos & Gareth O. Roberts & Alexandros Beskos & Paul Fearnhead, 2013. "Markov Chain Monte Carlo for Exact Inference for Diffusions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(2), pages 294-321, June.
  197. Ballarin, Giovanni & Dellaportas, Petros & Grigoryeva, Lyudmila & Hirt, Marcel & van Huellen, Sophie & Ortega, Juan-Pablo, 2024. "Reservoir computing for macroeconomic forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1206-1237.
  198. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2025. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Springer Books, in: Stepan Mazur & Pär Österholm (ed.), Recent Developments in Bayesian Econometrics and Their Applications, pages 89-115, Springer.
  199. Bretó, Carles, 2014. "On idiosyncratic stochasticity of financial leverage effects," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 20-26.
  200. Toby A. Patterson & Alison Parton & Roland Langrock & Paul G. Blackwell & Len Thomas & Ruth King, 2017. "Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(4), pages 399-438, October.
  201. Diana Giurghita & Dirk Husmeier, 2018. "Statistical modelling of cell movement," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 265-280, August.
  202. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
  203. Seuk Wai Phoong & Seuk Yen Phoong & Shi Ling Khek, 2022. "Systematic Literature Review With Bibliometric Analysis on Markov Switching Model: Methods and Applications," SAGE Open, , vol. 12(2), pages 21582440221, April.
  204. Owen Jamie & Wilkinson Darren J. & Gillespie Colin S., 2015. "Likelihood free inference for Markov processes: a comparison," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(2), pages 189-209, April.
  205. Hirokuni Iiboshi & Mototsugu Shintani & Kozo Ueda, 2022. "Estimating a Nonlinear New Keynesian Model with the Zero Lower Bound for Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(6), pages 1637-1671, September.
  206. Chan Joshua & Doucet Arnaud & León-González Roberto & Strachan Rodney W., 2025. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(3), pages 265-300.
  207. Hainaut, Donatien, 2017. "Contagion modeling between the financial and insurance markets with time changed processes," Insurance: Mathematics and Economics, Elsevier, vol. 74(C), pages 63-77.
  208. Liu Xiangdong & Li Xianglong & Zheng Shaozhi & Qian Hangyong, 2020. "PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps," Journal of Systems Science and Information, De Gruyter, vol. 8(2), pages 159-169, April.
  209. Karmakar, Sudipto & Lima, Diogo, 2023. "Global capital flows and the role of macroprudential policy," Journal of Financial Stability, Elsevier, vol. 67(C).
  210. Fulop, Andras & Heng, Jeremy & Li, Junye & Liu, Hening, 2022. "Bayesian estimation of long-run risk models using sequential Monte Carlo," Journal of Econometrics, Elsevier, vol. 228(1), pages 62-84.
  211. Zhang, Xing & Yan, Zhibin & Chen, Yunqi & Yuan, Yanhua, 2022. "A novel particle filter for extended target tracking with random hypersurface model," Applied Mathematics and Computation, Elsevier, vol. 425(C).
  212. Axel Finke & Ruth King & Alexandros Beskos & Petros Dellaportas, 2019. "Efficient Sequential Monte Carlo Algorithms for Integrated Population Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 204-224, June.
  213. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
  214. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
  215. Kien C. Tran & Panayotis G. Michaelides, 2025. "A class of generalized autoregressive score panel stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 64(3), pages 235-253, December.
  216. Christopher J. Gust & Edward P. Herbst & J. David López-Salido & Matthew E. Smith, 2012. "The Empirical Implications of the Interest-Rate Lower Bound," Finance and Economics Discussion Series 2012-83, Board of Governors of the Federal Reserve System (U.S.).
  217. McKinley, Trevelyan J. & Ross, Joshua V. & Deardon, Rob & Cook, Alex R., 2014. "Simulation-based Bayesian inference for epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 434-447.
  218. repec:plo:pcbi00:1006211 is not listed on IDEAS
  219. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
  220. Patrick Aschermayr & Konstantinos Kalogeropoulos, 2023. "Sequential Bayesian Learning for Hidden Semi-Markov Models," Papers 2301.10494, arXiv.org.
  221. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Bank of Russia Working Paper Series wps104, Bank of Russia.
  222. repec:rim:rimwps:18-23 is not listed on IDEAS
  223. David A Rasmussen & Erik M Volz & Katia Koelle, 2014. "Phylodynamic Inference for Structured Epidemiological Models," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-16, April.
  224. Andras Fulop & Jeremy Heng & Junye Li, 2022. "Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models," Papers 2201.01094, arXiv.org.
  225. Pitt, Michael K. & Silva, Ralph dos Santos & Giordani, Paolo & Kohn, Robert, 2012. "On some properties of Markov chain Monte Carlo simulation methods based on the particle filter," Journal of Econometrics, Elsevier, vol. 171(2), pages 134-151.
  226. Ephraim M. Hanks & Devin S. Johnson & Mevin B. Hooten, 2017. "Reflected Stochastic Differential Equation Models for Constrained Animal Movement," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(3), pages 353-372, September.
  227. Gunawan, David & Kohn, Robert & Tran, Minh Ngoc, 2025. "Flexible and Robust Particle Tempering for State Space Models," Econometrics and Statistics, Elsevier, vol. 33(C), pages 35-55.
  228. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 95-107.
  229. Ajay Jasra & Mohamed Maama & Aleksandar Mijatovi'c, 2024. "Modeling of Measurement Error in Financial Returns Data," Papers 2408.07405, arXiv.org.
  230. Faming Liang & Ick Hoon Jin & Qifan Song & Jun S. Liu, 2016. "An Adaptive Exchange Algorithm for Sampling From Distributions With Intractable Normalizing Constants," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 377-393, March.
  231. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
  232. Tsionas, Mike G., 2020. "On a model of environmental performance and technology gaps," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1141-1152.
  233. Carles Bret'o, 2013. "On idiosyncratic stochasticity of financial leverage effects," Papers 1312.5496, arXiv.org.
  234. repec:hum:wpaper:sfb649dp2012-008 is not listed on IDEAS
  235. Jesus Felipe & Manuel L. Albis, 2024. "Can the Philippines Attain 6.5-8 Percent Growth During 2023-28?: An Assessment Based on the Estimation of the Balance-of-Payments-Constrained Growth Rate," Economics Working Paper Archive wp_1039, Levy Economics Institute.
  236. repec:osf:thesis:4j3fu_v1 is not listed on IDEAS
  237. Kjartan Kloster Osmundsen & Tore Selland Kleppe & Roman Liesenfeld & Atle Oglend, 2021. "Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices," Econometrics, MDPI, vol. 9(4), pages 1-24, November.
  238. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2021. "Random variate generation for exponential and gamma tilted stable distributions," LSE Research Online Documents on Economics 108593, London School of Economics and Political Science, LSE Library.
  239. Kreuzer, Alexander & Dalla Valle, Luciana & Czado, Claudia, 2023. "Bayesian multivariate nonlinear state space copula models," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
  240. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
  241. Bhattacharya, Arnab & Wilson, Simon P., 2018. "Sequential Bayesian inference for static parameters in dynamic state space models," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 187-203.
  242. Laura Liu & Mikkel Plagborg-M?ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," CAEPR Working Papers 2021-001 Classification- , Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
  243. Han Chen & Yijie Fei & Jun Yu, 2026. "Multivariate Stochastic Volatility Model with Block Correlations," Working Papers 202638, University of Macau, Faculty of Business Administration.
  244. Piotr Szczepocki, 2020. "Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 173-187, June.
  245. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
  246. Chris Sherlock, 2016. "Optimal Scaling for the Pseudo-Marginal Random Walk Metropolis: Insensitivity to the Noise Generating Mechanism," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 869-884, September.
  247. Ruiz-Cárdenas, Ramiro & Krainski, Elias T. & Rue, Håvard, 2012. "Direct fitting of dynamic models using integrated nested Laplace approximations — INLA," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1808-1828.
  248. Gallant, A. Ronald & Giacomini, Raffaella & Ragusa, Giuseppe, 2017. "Bayesian estimation of state space models using moment conditions," Journal of Econometrics, Elsevier, vol. 201(2), pages 198-211.
  249. Mohammad R. Jahan-Parvar & Charles Knipp & Pawel J. Szerszen, 2024. "Trend-Cycle Decomposition and Forecasting Using Bayesian Multivariate Unobserved Components," Finance and Economics Discussion Series 2024-100, Board of Governors of the Federal Reserve System (U.S.).
  250. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
  251. Mike Tsionas & Subal C. Kumbhakar, 2024. "Endogenous Bad Outputs and Technical Inefficiency in U.S. Electric Utilities," The Energy Journal, , vol. 45(1), pages 149-171, January.
  252. Masaya M Saito & Hiroshi Nishiura & Tomoyuki Higuchi, 2018. "Reconstructing the transmission dynamics of rubella in Japan, 2012-2013," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
  253. Nima Nonejad, 2013. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," CREATES Research Papers 2013-27, Department of Economics and Business Economics, Aarhus University.
  254. Nguyen Ba Trung, 2024. "Exchange rate uncertainty and economic fluctuations in typical emerging economies," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 14(1), pages 88-103.
  255. Pierre Del Moral & Ajay Jasra & Yan Zhou, 2017. "Biased Online Parameter Inference for State-Space Models," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 727-749, September.
  256. Thomas Lux, 2022. "Bayesian Estimation of Agent-Based Models via Adaptive Particle Markov Chain Monte Carlo," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 451-477, August.
  257. Jonathan U Harrison & Ruth E Baker, 2018. "The impact of temporal sampling resolution on parameter inference for biological transport models," PLOS Computational Biology, Public Library of Science, vol. 14(6), pages 1-30, June.
  258. Xia, Tian & Zhou, Hang, 2023. "Commodity terms of trade co-movement: Global and regional factors," Journal of International Money and Finance, Elsevier, vol. 139(C).
  259. Patrick Leung & Catherine S. Forbes & Gael M. Martin & Brendan McCabe, 2016. "Data-driven particle Filters for particle Markov Chain Monte Carlo," Monash Econometrics and Business Statistics Working Papers 17/16, Monash University, Department of Econometrics and Business Statistics.
  260. Crucinio, Francesca R. & Johansen, Adam M., 2023. "Properties of marginal sequential Monte Carlo methods," Statistics & Probability Letters, Elsevier, vol. 203(C).
  261. Virbickaitė, Audronė & Frey, Christoph & Macedo, Demian N., 2020. "Bayesian sequential stock return prediction through copulas," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
  262. Delis, Manthos D. & Tsionas, Mike G., 2018. "Measuring management practices," International Journal of Production Economics, Elsevier, vol. 199(C), pages 65-77.
  263. Leigh Fisher & Jon Wakefield & Cici Bauer & Steve Self, 2017. "Time series modeling of pathogen-specific disease probabilities with subsampled data," Biometrics, The International Biometric Society, vol. 73(1), pages 283-293, March.
  264. Dureau, Joseph & Kalogeropoulos, Konstantinos & Baguelin, Marc, 2013. "Capturing the time-varying drivers of an epidemic using stochastic dynamical systems," LSE Research Online Documents on Economics 41749, London School of Economics and Political Science, LSE Library.
  265. Alessandri, Piergiorgio & Mumtaz, Haroon, 2025. "The macroeconomic cost of temperature risk," Journal of International Economics, Elsevier, vol. 158(C).
  266. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
  267. Bretó, Carles & Ionides, Edward L., 2011. "Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems," Stochastic Processes and their Applications, Elsevier, vol. 121(11), pages 2571-2591, November.
  268. Naoki Awaya & Yasuhiro Omori, 2019. "Particle rolling MCMC," CIRJE F-Series CIRJE-F-1110, CIRJE, Faculty of Economics, University of Tokyo.
  269. Golightly, Andrew & Bradley, Emma & Lowe, Tom & Gillespie, Colin S., 2019. "Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 92-107.
  270. Johan Dahlin & Thomas B. Schon, 2015. "Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models," Papers 1511.01707, arXiv.org, revised Mar 2019.
  271. David A Rasmussen & Oliver Ratmann & Katia Koelle, 2011. "Inference for Nonlinear Epidemiological Models Using Genealogies and Time Series," PLOS Computational Biology, Public Library of Science, vol. 7(8), pages 1-11, August.
  272. Charles Findling & Margaux Romand-Monnier & Vasilisa Skvortsova & Etienne Koechlin, 2025. "Neural variability in the medial prefrontal cortex contributes to efficient adaptive behavior," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
  273. Frank Schorfheide & Dongho Song & Amir Yaron, 2018. "Identifying Long‐Run Risks: A Bayesian Mixed‐Frequency Approach," Econometrica, Econometric Society, vol. 86(2), pages 617-654, March.
  274. Andreasen, Martin M., 2011. "Non-linear DSGE models and the optimized central difference particle filter," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1671-1695, October.
  275. Boschetti, Fabio & Vanderklift, Mathew A., 2015. "How the movement characteristics of large marine predators influence estimates of their abundance," Ecological Modelling, Elsevier, vol. 313(C), pages 223-236.
  276. Sergei Seleznev, 2016. "Solving DSGE models with stochastic trends," Bank of Russia Working Paper Series wps15, Bank of Russia.
  277. Gareth W. Peters & Rodrigo S. Targino & Mario V. Wüthrich, 2017. "Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks," Risks, MDPI, vol. 5(4), pages 1-51, September.
  278. Zdravko I. Botev & Pierre L’Ecuyer, 2020. "Sampling Conditionally on a Rare Event via Generalized Splitting," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 986-995, October.
  279. Takashi Kamihigashi & Hiroyuki Watanabe, 2016. "A Multiple-Try Extension of the Particle Marginal Metropolis-Hastings (PMMH) Algorithm with an Independent Proposal," Discussion Paper Series DP2016-36, Research Institute for Economics & Business Administration, Kobe University.
  280. David Lunn & Jessica Barrett & Michael Sweeting & Simon Thompson, 2013. "Fully Bayesian hierarchical modelling in two stages, with application to meta-analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 551-572, August.
  281. Sanda Micula, 2015. "Statistical Computer Simulations And Monte Carlo Methods," Journal of Information Systems & Operations Management, Romanian-American University, vol. 9(2), pages 384-394, December.
  282. Kleppe, Tore Selland & Oglend, Atle, 2017. "Estimating the competitive storage model: A simulated likelihood approach," Econometrics and Statistics, Elsevier, vol. 4(C), pages 39-56.
  283. Mumtaz, Haroon, 2018. "A generalised stochastic volatility in mean VAR," Economics Letters, Elsevier, vol. 173(C), pages 10-14.
  284. Giesecke, K. & Schwenkler, G., 2019. "Simulated likelihood estimators for discretely observed jump–diffusions," Journal of Econometrics, Elsevier, vol. 213(2), pages 297-320.
  285. Vergé, Christelle & Morio, Jérôme & Moral, Pierre Del, 2016. "An island particle algorithm for rare event analysis," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 63-75.
  286. repec:wyi:journl:002173 is not listed on IDEAS
  287. Gallant, A. Ronald & Hong, Han & Khwaja, Ahmed, 2018. "A Bayesian approach to estimation of dynamic models with small and large number of heterogeneous players and latent serially correlated states," Journal of Econometrics, Elsevier, vol. 203(1), pages 19-32.
  288. Umberto Picchini & Adeline Samson, 2018. "Coupling stochastic EM and approximate Bayesian computation for parameter inference in state-space models," Computational Statistics, Springer, vol. 33(1), pages 179-212, March.
  289. Naoki Awaya & Yasuhiro Omori, 2017. "Particle rolling MCMC with Double Block Sampling: Conditional SMC Update Approach," CIRJE F-Series CIRJE-F-1066, CIRJE, Faculty of Economics, University of Tokyo.
  290. Marín Díazaraque, Juan Miguel & Romero, Eva & Veiga, Helena, 2025. "Switching the leverage switch," DES - Working Papers. Statistics and Econometrics. WS 47005, Universidad Carlos III de Madrid. Departamento de Estadística.
  291. Joshua Chan & Rodney Strachan, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," CAMA Working Papers 2012-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  292. Fredrik Lindsten & Randal Douc & Eric Moulines, 2015. "Uniform Ergodicity of the Particle Gibbs Sampler," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 775-797, September.
  293. Karppinen, Santeri & Rajala, Tuomas & Mäntyniemi, Samu & Kojola, Ilpo & Vihola, Matti, 2022. "Identifying territories using presence-only citizen science data: An application to the Finnish wolf population," Ecological Modelling, Elsevier, vol. 472(C).
  294. Chon, Sora & Kim, Jaeho, 2021. "Does the Financial Leverage Effect Depend on Volatility Regimes?," Finance Research Letters, Elsevier, vol. 39(C).
  295. Nicolas Chopin & Mathieu Gerber, 2017. "Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes," Working Papers 2017-35, Center for Research in Economics and Statistics.
  296. Iryna Kaminska & Haroon Mumtaz, 2022. "Monetary policy transmission during QE times: role of expectations and term premia channels," Bank of England working papers 978, Bank of England.
  297. Shalini Sharma & Angshul Majumdar & Emilie Chouzenoux & Victor Elvira, 2023. "Deep State-Space Model for Predicting Cryptocurrency Price," Papers 2311.14731, arXiv.org.
  298. Axel Finke & Adam Johansen & Dario Spanò, 2014. "Static-parameter estimation in piecewise deterministic processes using particle Gibbs samplers," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(3), pages 577-609, June.
  299. Andras Fulop & Jun Yu, 2017. "Bayesian Analysis of Bubbles in Asset Prices," Econometrics, MDPI, vol. 5(4), pages 1-23, October.
  300. Fulop, Andras & Li, Junye, 2019. "Bayesian estimation of dynamic asset pricing models with informative observations," Journal of Econometrics, Elsevier, vol. 209(1), pages 114-138.
  301. Mike G. Tsionas & Nicholas Apergis, 2023. "Another look at contagion across United States and European financial markets: Evidence from the credit default swaps markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1137-1155, January.
  302. Wiqvist, Samuel & Golightly, Andrew & McLean, Ashleigh T. & Picchini, Umberto, 2021. "Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  303. Zhao, Yunfei & Gao, Wei & Smidts, Carol, 2021. "Sequential Bayesian inference of transition rates in the hidden Markov model for multi-state system degradation," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  304. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
  305. Rosen, Karol & Angeles-Camacho, César & Elvira, Víctor & Guillén-Burguete, Servio Tulio, 2023. "Intra-hour photovoltaic forecasting through a time-varying Markov switching model," Energy, Elsevier, vol. 278(PB).
  306. Pierre E. Jacob & John O’Leary & Yves F. Atchadé, 2020. "Unbiased Markov chain Monte Carlo methods with couplings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 543-600, July.
  307. Dimitrakopoulos, Stefanos & Tsionas, Mike G. & Aknouche, Abdelhakim, 2020. "Ordinal-response models for irregularly spaced transactions: A forecasting exercise," MPRA Paper 103250, University Library of Munich, Germany, revised 01 Oct 2020.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.