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Predictive Model Assessment for Count Data

Citations

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Cited by:

  1. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España.
  2. Peter Congdon, 2022. "A Model for Highly Fluctuating Spatio-Temporal Infection Data, with Applications to the COVID Epidemic," IJERPH, MDPI, vol. 19(11), pages 1-17, May.
  3. Søren Kjærgaard & Yunus Emre Ergemen & Malene Kallestrup-Lamb & Jim Oeppen & Rune Lindahl-Jacobsen, 2019. "Forecasting Causes of Death using Compositional Data Analysis: the Case of Cancer Deaths," CREATES Research Papers 2019-07, Department of Economics and Business Economics, Aarhus University.
  4. Moritz Berger & Gerhard Tutz, 2021. "Transition models for count data: a flexible alternative to fixed distribution models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1259-1283, October.
  5. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
  6. James Mitchell & Martin Weale, 2023. "Censored density forecasts: Production and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 714-734, August.
  7. Stephanie Glaser & Robert C. Jung & Karsten Schweikert, 2022. "Spatial panel count data: modeling and forecasting of urban crimes," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-29, December.
  8. Jean-François Richard, 2015. "Likelihood Based Inference and Prediction in Spatio-temporal Panel Count Models for Urban Crimes," Working Paper 5657, Department of Economics, University of Pittsburgh.
  9. Roel Verbelen & Katrien Antonio & Gerda Claeskens, 2018. "Unravelling the predictive power of telematics data in car insurance pricing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1275-1304, November.
  10. Kheifets, Igor & Velasco, Carlos, 2017. "New goodness-of-fit diagnostics for conditional discrete response models," Journal of Econometrics, Elsevier, vol. 200(1), pages 135-149.
  11. Shi, Peng & Feng, Xiaoping & Ivantsova, Anastasia, 2015. "Dependent frequency–severity modeling of insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 417-428.
  12. L. Held & K. Rufibach & F. Balabdaoui, 2010. "A Score Regression Approach to Assess Calibration of Continuous Probabilistic Predictions," Biometrics, The International Biometric Society, vol. 66(4), pages 1295-1305, December.
  13. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
  14. Qijin Cheng & Feng Chen & Paul S F Yip, 2017. "Media effects on suicide methods: A case study on Hong Kong 1998-2005," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-12, April.
  15. Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
  16. V. A. Alegana & C. Pezzulo & A. J. Tatem & B. Omar & A. Christensen, 2021. "Mapping out-of-school adolescents and youths in low- and middle-income countries," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
  17. Moizes Melo & Airlane Alencar, 2020. "Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 830-857, November.
  18. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
  19. Maffioli, Elisa M., 2021. "The political economy of health epidemics: Evidence from the Ebola outbreak," Journal of Development Economics, Elsevier, vol. 151(C).
  20. Catania, Leopoldo & Di Mari, Roberto, 2021. "Hierarchical Markov-switching models for multivariate integer-valued time-series," Journal of Econometrics, Elsevier, vol. 221(1), pages 118-137.
  21. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
  22. Kim M Pepin & Jia Wang & Colleen T Webb & Jennifer A Hoeting & Mary Poss & Peter J Hudson & Wenshan Hong & Huachen Zhu & Yi Guan & Steven Riley, 2013. "Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-8, February.
  23. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
  24. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
  25. Michael Höhle & Matthias an der Heiden, 2014. "Bayesian nowcasting during the STEC O104:H4 outbreak in Germany, 2011," Biometrics, The International Biometric Society, vol. 70(4), pages 993-1002, December.
  26. Frank van Berkum & Katrien Antonio & Michel Vellekoop, 2021. "Quantifying longevity gaps using micro‐level lifetime data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 548-570, April.
  27. Emily S Nightingale & Lloyd A C Chapman & Sridhar Srikantiah & Swaminathan Subramanian & Purushothaman Jambulingam & Johannes Bracher & Mary M Cameron & Graham F Medley, 2020. "A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(7), pages 1-21, July.
  28. Jiajie Kong & Robert Lund, 2023. "Seasonal count time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 93-124, January.
  29. 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.
  30. Euán, Carolina & Sun, Ying, 2020. "Bernoulli vector autoregressive model," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
  31. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
  32. Birgit Schrödle & Leonhard Held, 2011. "A primer on disease mapping and ecological regression using $${\texttt{INLA}}$$," Computational Statistics, Springer, vol. 26(2), pages 241-258, June.
  33. Xueli Wang & Moqin Zhou & Jinzhu Jia & Zhi Geng & Gexin Xiao, 2018. "A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases," IJERPH, MDPI, vol. 15(8), pages 1-13, August.
  34. Roman Liesenfeld & Jean‐François Richard & Jan Vogler, 2017. "Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 600-620, April.
  35. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
  36. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  37. Robert C. Jung & Stephanie Glaser, 2022. "Modelling and Diagnostics of Spatially Autocorrelated Counts," Econometrics, MDPI, vol. 10(3), pages 1-17, September.
  38. Birgit Schrödle & Leonhard Held & Håvard Rue, 2012. "Assessing the Impact of a Movement Network on the Spatiotemporal Spread of Infectious Diseases," Biometrics, The International Biometric Society, vol. 68(3), pages 736-744, September.
  39. Vasiliki Christou & Konstantinos Fokianos, 2014. "Quasi-Likelihood Inference For Negative Binomial Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 55-78, January.
  40. Nicholas G. Reich & Justin Lessler & Krzysztof Sakrejda & Stephen A. Lauer & Sopon Iamsirithaworn & Derek A. T. Cummings, 2016. "Case Study in Evaluating Time Series Prediction Models Using the Relative Mean Absolute Error," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 285-292, July.
  41. G. Vicente & T. Goicoa & P. Fernandez‐Rasines & M. D. Ugarte, 2020. "Crime against women in India: unveiling spatial patterns and temporal trends of dowry deaths in the districts of Uttar Pradesh," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 655-679, February.
  42. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
  43. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
  44. Nisreen Shamma & Mehrnaz Mohammadpour & Masoumeh Shirozhan, 2020. "A time series model based on dependent zero inflated counting series," Computational Statistics, Springer, vol. 35(4), pages 1737-1757, December.
  45. Wagner Barreto‐Souza & Hernando Ombao, 2022. "The negative binomial process: A tractable model with composite likelihood‐based inference," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 568-592, June.
  46. Cui, Yunwei & Wu, Rongning, 2016. "On conditional maximum likelihood estimation for INGARCH(p,q) models," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 1-7.
  47. Ateca-Amestoy, Victoria & Prieto-Rodriguez, Juan, 2013. "Forecasting accuracy of behavioural models for participation in the arts," European Journal of Operational Research, Elsevier, vol. 229(1), pages 124-131.
  48. Gao, Lisa & Shi, Peng, 2022. "Leveraging high-resolution weather information to predict hail damage claims: A spatial point process for replicated point patterns," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 161-179.
  49. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
  50. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
  51. Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
  52. László Martinek, 2019. "Analysis of Stochastic Reserving Models By Means of NAIC Claims Data," Risks, MDPI, vol. 7(2), pages 1-27, June.
  53. Christopher Gelpi & Nazli Avdan, 2018. "Democracies at risk? A forecasting analysis of regime type and the risk of terrorist attack," Conflict Management and Peace Science, Peace Science Society (International), vol. 35(1), pages 18-42, January.
  54. Wei Wei & Leonhard Held, 2014. "Calibration tests for count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 787-805, December.
  55. Braun, Julia & Sabanés Bové, Daniel & Held, Leonhard, 2014. "Choice of generalized linear mixed models using predictive crossvalidation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 190-202.
  56. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
  57. Munro, Alastair D. & Smallman-Raynor, Matthew & Algar, Adam C., 2021. "Long-term changes in endemic threshold populations for pertussis in England and Wales: A spatiotemporal analysis of Lancashire and South Wales, 1940-69," Social Science & Medicine, Elsevier, vol. 288(C).
  58. Sarlo, Rodrigo & Fernandes, Cristiano & Borenstein, Denis, 2023. "Lumpy and intermittent retail demand forecasts with score-driven models," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1146-1160.
  59. Robert C. Jung & Andrew R. Tremayne, 2020. "Maximum-Likelihood Estimation in a Special Integer Autoregressive Model," Econometrics, MDPI, vol. 8(2), pages 1-15, June.
  60. Kessler, Jeff & Sperling, Daniel, 2016. "Tracking U.S. biofuel innovation through patents," Energy Policy, Elsevier, vol. 98(C), pages 97-107.
  61. Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
  62. Bracher, Johannes & Held, Leonhard, 2022. "Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1221-1233.
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