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Direct calculation of the information matrix via the EM

Citations

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Cited by:

  1. Di Mari, Roberto & Bakk, Zsuzsa & Oser, Jennifer & Kuha, Jouni, 2023. "A two-step estimator for multilevel latent class analysis with covariates," LSE Research Online Documents on Economics 119994, London School of Economics and Political Science, LSE Library.
  2. De Blander, Rembert, 2020. "Iterative estimation correcting for error auto-correlation in short panels, applied to lagged dependent variable models," Econometrics and Statistics, Elsevier, vol. 15(C), pages 3-29.
  3. Hartley, Roger & Lanot, Gauthier, 2006. "Heterogeneous demand responses to discrete price changes: an application to the purchase of lottery tickets," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 859-877, February.
  4. Qingyang Liu & Xianzheng Huang & Haiming Zhou, 2024. "The Flexible Gumbel Distribution: A New Model for Inference about the Mode," Stats, MDPI, vol. 7(1), pages 1-16, March.
  5. Budhi Arta Surya, 2021. "Some results on maximum likelihood from incomplete data: finite sample properties and improved M-estimator for resampling," Papers 2108.01243, arXiv.org, revised Jul 2022.
  6. Chong-Zhi Di & Karen Bandeen-Roche, 2011. "Multilevel Latent Class Models with Dirichlet Mixing Distribution," Biometrics, The International Biometric Society, vol. 67(1), pages 86-96, March.
  7. Shu Yang & Jae Kwang Kim, 2016. "Likelihood-based Inference with Missing Data Under Missing-at-Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 436-454, June.
  8. McLain, Alexander C. & Zgodic, Anja & Bondell, Howard, 2025. "Efficient sparse high-dimensional linear regression with a partitioned empirical Bayes ECM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 207(C).
  9. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
  10. Dalila Failli & Maria Francesca Marino & Francesca Martella, 2025. "A Novel Approach for Biclustering Bipartite Networks: An Extension of Finite Mixtures of Latent Trait Analyzers," Journal of Classification, Springer;The Classification Society, vol. 42(3), pages 492-516, November.
  11. Bartolucci, Francesco & Pandolfi, Silvia & Pennoni, Fulvia, 2025. "On a class of finite mixture models that includes hidden Markov models," Journal of Multivariate Analysis, Elsevier, vol. 208(C).
  12. Alessio Farcomeni, 2015. "Latent class recapture models with flexible behavioural response," Statistica, Department of Statistics, University of Bologna, vol. 75(1), pages 5-17.
  13. Jouni Kuha & Jonathan Jackson, 2014. "The item count method for sensitive survey questions: modelling criminal behaviour," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(2), pages 321-341, February.
  14. Maria Giovanna Ranalli & Fulvia Pennoni & Francesco Bartolucci & Antonietta Mira, 2025. "When non-response makes estimates from a census a small area estimation problem: the case of the survey on graduates’ employment status in Italy," 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. 19(2), pages 515-543, June.
  15. Yong Li & Zeng Tao & Jun Yu, "undated". "Robust Deviance Information Criterion for Latent Variable Models," Working Papers CoFie-04-2012, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
  16. Zhou, Lin & Tang, Yayong, 2021. "Linearly preconditioned nonlinear conjugate gradient acceleration of the PX-EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
  17. Arvid Raknerud & Terje Skjerpen & Anders Swensen, 2007. "A linear demand system within a seemingly unrelated time series equations framework," Empirical Economics, Springer, vol. 32(1), pages 105-124, April.
  18. Turner, Rolf, 2008. "Direct maximization of the likelihood of a hidden Markov model," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4147-4160, May.
  19. Rosaria Simone, 2021. "An accelerated EM algorithm for mixture models with uncertainty for rating data," Computational Statistics, Springer, vol. 36(1), pages 691-714, March.
  20. Doğan, Osman & Taşpınar, Süleyman & Bera, Anil K., 2021. "A Bayesian robust chi-squared test for testing simple hypotheses," Journal of Econometrics, Elsevier, vol. 222(2), pages 933-958.
  21. Giorgio Eduardo Montanari & Marco Doretti & Maria Francesca Marino, 2022. "Model-based two-way clustering of second-level units in ordinal multilevel latent Markov models," 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. 16(2), pages 457-485, June.
  22. Yuzhu Tian & Manlai Tang & Yanchao Zang & Maozai Tian, 2018. "Quantile regression for linear models with autoregressive errors using EM algorithm," Computational Statistics, Springer, vol. 33(4), pages 1605-1625, December.
  23. Gordon Anderson & Alessio Farcomeni & Grazia Pittau & Roberto Zelli, 2014. "A new approach to measuring and studying the characteristics of class membership: The progress of poverty, inequality and polarization of income classes in urban China," Working Papers tecipa-521, University of Toronto, Department of Economics.
  24. David Aristei & Silvia Bacci & Francesco Bartolucci & Silvia Pandolfi, 2021. "A bivariate finite mixture growth model with selection," 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. 15(3), pages 759-793, September.
  25. Gauthier Lanot, 2002. "On the Variance Covariance Matrix of the Maximum Likelihood Estimator of a Discrete Mixture," Keele Economics Research Papers KERP 2002/07, Centre for Economic Research, Keele University.
  26. Deb Partha & Trivedi Pravin K., 2013. "Finite Mixture for Panels with Fixed Effects," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 35-51, July.
  27. Linda Möstel & Marius Pfeuffer & Matthias Fischer, 2020. "Statistical inference for Markov chains with applications to credit risk," Computational Statistics, Springer, vol. 35(4), pages 1659-1684, December.
  28. Tian, Yuzhu & Zhu, Qianqian & Tian, Maozai, 2016. "Estimation of linear composite quantile regression using EM algorithm," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 183-191.
  29. R. Philip Chalmers, 2018. "Model-Based Measures for Detecting and Quantifying Response Bias," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 696-732, September.
  30. Greig Smith & Goncalo dos Reis, 2017. "Robust and Consistent Estimation of Generators in Credit Risk," Papers 1702.08867, arXiv.org, revised Oct 2017.
  31. Björn Andersson & Tao Xin, 2021. "Estimation of Latent Regression Item Response Theory Models Using a Second-Order Laplace Approximation," Journal of Educational and Behavioral Statistics, , vol. 46(2), pages 244-265, April.
  32. Sanjeev K Tomer & M S Panwar & Himanshu Rai, 2025. "A Latent Variable Approach to the Analysis of Progressively Hybrid Censored Masked Data," Methodology and Computing in Applied Probability, Springer, vol. 27(4), pages 1-28, December.
  33. Felix Zimmer & Clemens Draxler & Rudolf Debelak, 2023. "Power Analysis for the Wald, LR, Score, and Gradient Tests in a Marginal Maximum Likelihood Framework: Applications in IRT," Psychometrika, Springer;The Psychometric Society, vol. 88(4), pages 1249-1298, December.
  34. Roberto Mari & Zsuzsa Bakk & Jennifer Oser & Jouni Kuha, 2023. "A two-step estimator for multilevel latent class analysis with covariates," Psychometrika, Springer;The Psychometric Society, vol. 88(4), pages 1144-1170, December.
  35. Robben, Jens & Barigou, Karim & Kleinow, Torsten, 2025. "Granular mortality modeling with temperature and epidemic shocks: a three-state regime-switching approach," LIDAM Discussion Papers ISBA 2025006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  36. Li, Yong & Zeng, Tao & Yu, Jun, 2014. "A new approach to Bayesian hypothesis testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 602-612.
  37. Nguyen, Thu Thuy & Mentré, France, 2014. "Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 57-69.
  38. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
  39. Bacci, Silvia & Bartolucci, Francesco & Pieroni, Luca, 2012. "A causal analysis of mother’s education on birth inequalities," MPRA Paper 38754, University Library of Munich, Germany.
  40. Marius Pfeuffer & Goncalo dos Reis & Greig smith, 2018. "Capturing Model Risk and Rating Momentum in the Estimation of Probabilities of Default and Credit Rating Migrations," Papers 1809.09889, arXiv.org, revised Feb 2020.
  41. Anderson, Gordon & Farcomeni, Alessio & Pittau, Maria Grazia & Zelli, Roberto, 2016. "A new approach to measuring and studying the characteristics of class membership: Examining poverty, inequality and polarization in urban China," Journal of Econometrics, Elsevier, vol. 191(2), pages 348-359.
  42. Yilong Zhang & Xiaoxia Han & Yongzhao Shao, 2021. "The ROC of Cox proportional hazards cure models with application in cancer studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(2), pages 195-215, April.
  43. Mogens Bladt & Michael SØrensen, 2009. "Efficient estimation of transition rates between credit ratings from observations at discrete time points," Quantitative Finance, Taylor & Francis Journals, vol. 9(2), pages 147-160.
  44. Roberto Colombi & Sabrina Giordano & Maria Kateri, 2024. "Hidden Markov models for longitudinal rating data with dynamic response styles," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(1), pages 1-36, March.
  45. Framba, Matteo & Vinciotti, Veronica & Wit, Ernst C., 2024. "Latent event history models for quasi-reaction systems," Computational Statistics & Data Analysis, Elsevier, vol. 198(C).
  46. Giorgio E. Montanari & Marco Doretti, 2019. "Ranking Nursing Homes’ Performances Through a Latent Markov Model with Fixed and Random Effects," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 307-326, November.
  47. Tan, Ming & Tian, Guo-Liang & Wang Ng, Kai, 2006. "Hierarchical models for repeated binary data using the IBF sampler," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1272-1286, March.
  48. Herwig Friedl & Göran Kauermann, 2000. "Standard Errors for EM Estimates in Generalized Linear Models with Random Effects," Biometrics, The International Biometric Society, vol. 56(3), pages 761-767, September.
  49. Zhao, Xiujie & Chen, Piao & Gaudoin, Olivier & Doyen, Laurent, 2021. "Accelerated degradation tests with inspection effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1099-1114.
  50. Kaiqiong Zhao & Karim Oualkacha & Lajmi Lakhal‐Chaieb & Aurélie Labbe & Kathleen Klein & Antonio Ciampi & Marie Hudson & Inés Colmegna & Tomi Pastinen & Tieyuan Zhang & Denise Daley & Celia M.T. Green, 2021. "A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation," Biometrics, The International Biometric Society, vol. 77(2), pages 424-438, June.
  51. Regier Michael D. & Moodie Erica E. M., 2016. "The Orthogonally Partitioned EM Algorithm: Extending the EM Algorithm for Algorithmic Stability and Bias Correction Due to Imperfect Data," The International Journal of Biostatistics, De Gruyter, vol. 12(1), pages 65-77, May.
  52. Yuzhu Tian & Manlai Tang & Maozai Tian, 2016. "A class of finite mixture of quantile regressions with its applications," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(7), pages 1240-1252, July.
  53. Scott Monroe, 2019. "Estimation of Expected Fisher Information for IRT Models," Journal of Educational and Behavioral Statistics, , vol. 44(4), pages 431-447, August.
  54. F. Bartolucci & A. Farcomeni & F. Pennoni, 2014. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 433-465, September.
  55. Printechapat, Tanes & Aiewsakun, Pakorn & Krityakierne, Tipaluck, 2025. "Caged Markov process – A continuous-time framework for modeling a constrained Markov process within a freely-evolving Markov process," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 230(C), pages 350-369.
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