IDEAS home Printed from https://ideas.repec.org/r/cup/cbooks/9780521852258.html
   My bibliography  Save this item

Model Selection and Model Averaging

Citations

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


Cited by:

  1. Jäckel, Christoph, 2013. "Model uncertainty and expected return proxies," MPRA Paper 51978, University Library of Munich, Germany.
  2. Nils Lid Hjort & Emil Aas Stoltenberg, 2023. "The partly parametric and partly nonparametric additive risk model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 372-402, April.
  3. Phillip Heiler & Jana Mareckova, 2019. "Shrinkage for Categorical Regressors," Papers 1901.01898, arXiv.org.
  4. John Copas & Shinto Eguchi, 2020. "Strong model dependence in statistical analysis: goodness of fit is not enough for model choice," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(2), pages 329-352, April.
  5. Rockey, James & Temple, Jonathan, 2016. "Growth econometrics for agnostics and true believers," European Economic Review, Elsevier, vol. 81(C), pages 86-102.
  6. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Luigi Montrucchio, 2011. "Classical Subjective Expected Utility," Working Papers 400, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  7. Jan A. van den Brakel & Bart Buelens, 2015. "Covariate Selection For Small Area Estimation In Repeated Sample Surveys," Statistics in Transition New Series, Polish Statistical Association, vol. 16(4), pages 523-540, December.
  8. Michael Vogt & Oliver Linton, 2014. "Nonparametric estimation of a periodic sequence in the presence of a smooth trend," Biometrika, Biometrika Trust, vol. 101(1), pages 121-140.
  9. Søren Johansen & Marco Riani & Anthony C. Atkinson, 2012. "The Selection of ARIMA Models with or without Regressors," Discussion Papers 12-17, University of Copenhagen. Department of Economics.
  10. Rolina D. van Gaalen & Michal Abrahamowicz & David L. Buckeridge, 2017. "Using Multiple Pharmacovigilance Models Improves the Timeliness of Signal Detection in Simulated Prospective Surveillance," Drug Safety, Springer, vol. 40(11), pages 1119-1129, November.
  11. Baglan, Deniz & Ege Yazgan, M. & Yilmazkuday, Hakan, 2016. "Relative price variability and inflation: New evidence," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 263-282.
  12. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  13. Arthur Novaes de Amorim & Rob Deardon & Vineet Saini, 2021. "A stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-15, March.
  14. Paul Kabaila & A. H. Welsh & Waruni Abeysekera, 2016. "Model-Averaged Confidence Intervals," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 35-48, March.
  15. Shoichi Eguchi & Yuma Uehara, 2021. "Schwartz‐type model selection for ergodic stochastic differential equation models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(3), pages 950-968, September.
  16. Ivana Lolić & Petar Sorić & Marija Logarušić, 2022. "Economic Policy Uncertainty Index Meets Ensemble Learning," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 401-437, August.
  17. Guozhi Hu & Weihu Cheng & Jie Zeng, 2023. "Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
  18. Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series 305, Institute for Advanced Studies.
  19. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
  20. Nubyra Ahmed & Sundarraman Subramanian, 2016. "Semiparametric simultaneous confidence bands for the difference of survival functions," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(4), pages 504-530, October.
  21. J. Cao & L. Wang & J. Xu, 2011. "Robust Estimation for Ordinary Differential Equation Models," Biometrics, The International Biometric Society, vol. 67(4), pages 1305-1313, December.
  22. Hjort, Nils Lid & McKeague, Ian W. & Van Keilegom, Ingrid, 2017. "Hybrid combinations of parametric and empirical likelihoods," LIDAM Discussion Papers ISBA 2017021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  23. José Manuel Cordero Ferrera & Manuel Muñiz Pérez & Rosa Simancas Rodríguez, 2015. "The influence of socioeconomic factors on cognitive and non-cognitive educational outcomes," Investigaciones de Economía de la Educación volume 10, in: Marta Rahona López & Jennifer Graves (ed.), Investigaciones de Economía de la Educación 10, edition 1, volume 10, chapter 21, pages 413-438, Asociación de Economía de la Educación.
  24. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
  25. Satoshi Hattori & Masayuki Henmi, 2014. "Stratified doubly robust estimators for the average causal effect," Biometrics, The International Biometric Society, vol. 70(2), pages 270-277, June.
  26. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.
  27. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
  28. VÁZQUEZ-ALCOCER, Alan & SCHOEN, Eric D. & GOOS, Peter, 2018. "A mixed integer optimization approach for model selection in screening experiments," Working Papers 2018007, University of Antwerp, Faculty of Business and Economics.
  29. Mark P Little & Alexander G Kukush & Sergii V Masiuk & Sergiy Shklyar & Raymond J Carroll & Jay H Lubin & Deukwoo Kwon & Alina V Brenner & Mykola D Tronko & Kiyohiko Mabuchi & Tetiana I Bogdanova & Ma, 2014. "Impact of Uncertainties in Exposure Assessment on Estimates of Thyroid Cancer Risk among Ukrainian Children and Adolescents Exposed from the Chernobyl Accident," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-9, January.
  30. Céline Cunen & Nils Lid Hjort, 2022. "Combining information across diverse sources: The II‐CC‐FF paradigm," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 625-656, June.
  31. Chung‐Wei Shen & Yi‐Hau Chen, 2018. "Model selection for semiparametric marginal mean regression accounting for within‐cluster subsampling variability and informative cluster size," Biometrics, The International Biometric Society, vol. 74(3), pages 934-943, September.
  32. Robert J. B. Goudie & Sach Mukherjee & Jan-Emmanuel De Neve & Andrew J. Oswald & Stephen Wu, 2011. "Happiness as a Driver of Risk-Avoiding Behavior," CESifo Working Paper Series 3451, CESifo.
  33. Steffen Grønneberg & Nils Lid Hjort, 2014. "The Copula Information Criteria," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 436-459, June.
  34. Jingwen Tu & Hu Yang & Chaohui Guo & Jing Lv, 2021. "Model averaging marginal regression for high dimensional conditional quantile prediction," Statistical Papers, Springer, vol. 62(6), pages 2661-2689, December.
  35. Jeffrey S. Racine & Qi Li & Dalei Yu & Li Zheng, 2023. "Optimal Model Averaging of Mixed-Data Kernel-Weighted Spline Regressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1251-1261, October.
  36. Andrew Neath & Joseph Cavanaugh & Adam Weyhaupt, 2015. "Model evaluation, discrepancy function estimation, and social choice theory," Computational Statistics, Springer, vol. 30(1), pages 231-249, March.
  37. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
  38. Zhang, Xinyu & Liu, Chu-An, 2023. "Model averaging prediction by K-fold cross-validation," Journal of Econometrics, Elsevier, vol. 235(1), pages 280-301.
  39. I.M.L. Nadeesha Jayaweera & A. Alexandre Trindade, 2024. "How Certain are You of Your Minimum AIC or BIC Values?," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(2), pages 880-919, August.
  40. Carlo Baldassi & Alireza Alemi-Neissi & Marino Pagan & James J DiCarlo & Riccardo Zecchina & Davide Zoccolan, 2013. "Shape Similarity, Better than Semantic Membership, Accounts for the Structure of Visual Object Representations in a Population of Monkey Inferotemporal Neurons," PLOS Computational Biology, Public Library of Science, vol. 9(8), pages 1-20, August.
  41. Julien Chevallier & Mathieu Gatumel & Florian Ielpo, 2014. "Commodity markets through the business cycle," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1597-1618, September.
  42. Raffaella Giacomini & Toru Kitagawa & Alessio Volpicella, 2022. "Uncertain identification," Quantitative Economics, Econometric Society, vol. 13(1), pages 95-123, January.
  43. Robin C. Sickles & Jiaqi Hao & Chenjun Shang, 2014. "Panel data and productivity measurement: an analysis of Asian productivity trends," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 12(3), pages 211-231, August.
  44. S. C. Pandhare & T. V. Ramanathan, 2020. "The focussed information criterion for generalised linear regression models for time series," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 485-507, December.
  45. Chen, Yi-Ting & Liu, Chu-An, 2023. "Model averaging for asymptotically optimal combined forecasts," Journal of Econometrics, Elsevier, vol. 235(2), pages 592-607.
  46. Liu, Chu-An, 2012. "A plug-in averaging estimator for regressions with heteroskedastic errors," MPRA Paper 41414, University Library of Munich, Germany.
  47. Naoya Sueishi & Arihiro Yoshimura, 2017. "Focused Information Criterion for Series Estimation in Partially Linear Models," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 352-363, September.
  48. Imad Bou-Hamad & Abdel Latef Anouze & Denis Larocque, 2017. "An integrated approach of data envelopment analysis and boosted generalized linear mixed models for efficiency assessment," Annals of Operations Research, Springer, vol. 253(1), pages 77-95, June.
  49. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
  50. B. Karmakar & K. Dhara & K. Dey & A. Basu & A. Ghosh, 2015. "Tests for statistical significance of a treatment effect in the presence of hidden sub-populations," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 97-119, March.
  51. Marcio Laurini, 2011. "Bayesian Factor Selection in Dynamic Term Structure Models," Economics Bulletin, AccessEcon, vol. 31(3), pages 2167-2176.
  52. Messner, Wolfgang, 2023. "The contingency impact of culture on health security capacities for pandemic preparedness: A moderated Bayesian inference analysis," Journal of International Management, Elsevier, vol. 29(5).
  53. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
  54. Katrin Wölfel & Christoph S. Weber, 2017. "Searching for the Fed’s reaction function," Empirical Economics, Springer, vol. 52(1), pages 191-227, February.
  55. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
  56. Wei, Yuting & Wang, Qihua & Duan, Xiaogang & Qin, Jing, 2021. "Bias-corrected Kullback–Leibler distance criterion based model selection with covariables missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
  57. Mitra Robin & Dunson David, 2010. "Two-Level Stochastic Search Variable Selection in GLMs with Missing Predictors," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-40, October.
  58. Julia Braun & Leonhard Held & Bruno Ledergerber, 2012. "Predictive Cross-validation for the Choice of Linear Mixed-Effects Models with Application to Data from the Swiss HIV Cohort Study," Biometrics, The International Biometric Society, vol. 68(1), pages 53-61, March.
  59. Massimiliano Mazzanti & Antonio Musolesi, 2020. "Modeling Green Knowledge Production and Environmental Policies with Semiparametric Panel Data Regression models," SEEDS Working Papers 1420, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Sep 2020.
  60. David Kaplan, 2021. "On the Quantification of Model Uncertainty: A Bayesian Perspective," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 215-238, March.
  61. Alexandra Ferreira‐Lopes & Pedro Linhares & Luís Filipe Martins & Tiago Neves Sequeira, 2022. "Quantitative easing and economic growth in Japan: A meta‐analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 235-268, February.
  62. Ortelli, Nicola & Hillel, Tim & Pereira, Francisco C. & de Lapparent, Matthieu & Bierlaire, Michel, 2021. "Assisted specification of discrete choice models," Journal of choice modelling, Elsevier, vol. 39(C).
  63. Paul Lukacs & Kenneth Burnham & David Anderson, 2010. "Model selection bias and Freedman’s paradox," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 117-125, February.
  64. Bhattacharya, Debopam & Dupas, Pascaline, 2012. "Inferring welfare maximizing treatment assignment under budget constraints," Journal of Econometrics, Elsevier, vol. 167(1), pages 168-196.
  65. Zhang, Xiang & Rasmussen, Christoffer & Saelens, Dirk & Roels, Staf, 2022. "Time-dependent solar aperture estimation of a building: Comparing grey-box and white-box approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  66. Liao, Jun & Zou, Guohua, 2020. "Corrected Mallows criterion for model averaging," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  67. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
  68. Ogasawara, Haruhiko, 2017. "Expected predictive least squares for model selection in covariance structures," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 151-164.
  69. De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2018. "Weighted-average least squares estimation of generalized linear models," Journal of Econometrics, Elsevier, vol. 204(1), pages 1-17.
  70. W. M. Tang & K. F. C. Yiu & H. Wong, 2020. "Subset Selection Using Frequency Decomposition with Applications," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 195-220, March.
  71. Davide Fiaschi & Andrea Mario Lavezzi & Angela Parenti, 2020. "Deep and Proximate Determinants of the World Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(3), pages 677-710, September.
  72. Zhang, Xiang & Saelens, Dirk & Roels, Staf, 2022. "Estimating dynamic solar gains from on-site measured data: An ARX modelling approach," Applied Energy, Elsevier, vol. 321(C).
  73. Korprasertsak, Natapol & Leephakpreeda, Thananchai, 2019. "Robust short-term prediction of wind power generation under uncertainty via statistical interpretation of multiple forecasting models," Energy, Elsevier, vol. 180(C), pages 387-397.
  74. José A. Tapia Granados & Edward L. Ionides, 2011. "Mortality and Macroeconomic Fluctuations in Contemporary Sweden [Mortalité et fluctuations macroéconomiques dans la Suède contemporaine]," European Journal of Population, Springer;European Association for Population Studies, vol. 27(2), pages 157-184, May.
  75. Ogasawara, Haruhiko, 2016. "Bias correction of the Akaike information criterion in factor analysis," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 144-159.
  76. Fischer, Manfred M. & Piribauer, Philipp, 2013. "Model uncertainty in matrix exponential spatial growth regression models," Department of Economics Working Paper Series 158, WU Vienna University of Economics and Business.
  77. Matthew W. Wheeler & Jose Cortiñas Abrahantes & Marc Aerts & Jeffery S. Gift & Jerry Allen Davis, 2022. "Continuous model averaging for benchmark dose analysis: Averaging over distributional forms," Environmetrics, John Wiley & Sons, Ltd., vol. 33(5), August.
  78. Julian Rossbroich & Jeffrey Durieux & Tom F. Wilderjans, 2022. "Model Selection Strategies for Determining the Optimal Number of Overlapping Clusters in Additive Overlapping Partitional Clustering," Journal of Classification, Springer;The Classification Society, vol. 39(2), pages 264-301, July.
  79. Martínez-Zarzoso, Inmaculada & Maruotti, Antonello, 2011. "The impact of urbanization on CO2 emissions: Evidence from developing countries," Ecological Economics, Elsevier, vol. 70(7), pages 1344-1353, May.
  80. Yongxin Liu & Peng Zeng & Lu Lin, 2021. "Degrees of freedom for regularized regression with Huber loss and linear constraints," Statistical Papers, Springer, vol. 62(5), pages 2383-2405, October.
  81. Katleho Daniel Makatjane & Edward Kagiso Molefe & Roscoe Bertrum van Wyk, 2018. "The Analysis of the 2008 US Financial Crisis: An Intervention Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 10(1), pages 59-68.
  82. L.H.A. Dal Bello & A. F.C. Vieira, 2011. "Optimization of a product performance using mixture experiments including process variables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1701-1715, August.
  83. Jiun-Hua Su, 2019. "Model Selection in Utility-Maximizing Binary Prediction," Papers 1903.00716, arXiv.org, revised Jul 2020.
  84. Samuel Müller & Alan H. Welsh, 2010. "On Model Selection Curves," International Statistical Review, International Statistical Institute, vol. 78(2), pages 240-256, August.
  85. Candida Geerdens & Gerda Claeskens & Paul Janssen, 2016. "Copula based flexible modeling of associations between clustered event times," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(3), pages 363-381, July.
  86. Tune H Pers & Anders Albrechtsen & Claus Holst & Thorkild I A Sørensen & Thomas A Gerds, 2009. "The Validation and Assessment of Machine Learning: A Game of Prediction from High-Dimensional Data," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-8, August.
  87. Andrea C. Garcia‐Angulo & Gerda Claeskens, 2023. "Exact uniformly most powerful postselection confidence distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 358-382, March.
  88. Fantazzini, Dean & Shakleina, Marina & Yuras, Natalia, 2018. "Big Data for computing social well-being indices of the Russian population," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 50, pages 43-66.
  89. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
  90. Riani, Marco & Atkinson, Anthony Curtis & Corbellini, Aldo & Farcomeni, Alessio & Laurini, Fabrizio, 2024. "Information Criteria for Outlier Detection Avoiding Arbitrary Significance Levels," Econometrics and Statistics, Elsevier, vol. 29(C), pages 189-205.
  91. Federica Onori & Giovanna Jona Lasinio, 2022. "Modeling “Equitable and Sustainable Well-being” (BES) Using Bayesian Networks: A Case Study of the Italian Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 1003-1037, June.
  92. Bhattacharya, Rianka & Subramanian, Sundarraman, 2014. "Two-sample location–scale estimation from semiparametric random censorship models," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 25-38.
  93. Federico Grasselli & Stefano Baroni, 2021. "Invariance principles in the theory and computation of transport coefficients," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(8), pages 1-14, August.
  94. Miao Han & Liuquan Sun & Yutao Liu & Jun Zhu, 2018. "Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 523-547, July.
  95. Lasanthi C. R. Pelawa Watagoda & David J. Olive, 2021. "Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals," Statistical Papers, Springer, vol. 62(5), pages 2407-2431, October.
  96. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova, 2018. "Exchange rate forecasting and the performance of currency portfolios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 519-540, August.
  97. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
  98. Fenyang Tang & Yuejia Cheng & Changjun Bao & Jianli Hu & Wendong Liu & Qi Liang & Ying Wu & Jessie Norris & Zhihang Peng & Rongbin Yu & Hongbing Shen & Feng Chen, 2014. "Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
  99. Guillaume Allaire Pouliot & Zhen Xie, 2022. "Degrees of Freedom and Information Criteria for the Synthetic Control Method," Papers 2207.02943, arXiv.org.
  100. G. Avlogiaris & A. C. Micheas & K. Zografos, 2019. "A Criterion for Local Model Selection," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 406-444, December.
  101. Giuseppe Luca & Jan R. Magnus & Franco Peracchi, 2023. "Weighted-Average Least Squares (WALS): Confidence and Prediction Intervals," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1637-1664, April.
  102. Hai Wang & Xinjie Chen & Nancy Flournoy, 2016. "The focused information criterion for varying-coefficient partially linear measurement error models," Statistical Papers, Springer, vol. 57(1), pages 99-113, March.
  103. Fabio Canova & Christian Matthes, 2021. "Dealing with misspecification in structural macroeconometric models," Quantitative Economics, Econometric Society, vol. 12(2), pages 313-350, May.
  104. Chang, Yung-Chi & Enkhjargal, Uguumur & Huang, Chen-I & Lin, Wen-Ling & Ho, Chi-Ming, 2020. "Factors Affecting the Internet Banking Adoption," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 54(3), pages 117-131.
  105. Wagner Martin & Hlouskova Jaroslava, 2015. "Growth Regressions, Principal Components Augmented Regressions and Frequentist Model Averaging," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(6), pages 642-662, December.
  106. Andrea Cappozzo & Luis Angel García Escudero & Francesca Greselin & Agustín Mayo-Iscar, 2021. "Parameter Choice, Stability and Validity for Robust Cluster Weighted Modeling," Stats, MDPI, vol. 4(3), pages 1-14, July.
  107. Yu, Jun & Meng, Xiran & Wang, Yaping, 2023. "Optimal designs for semi-parametric dose-response models under random contamination," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
  108. Qi, Hang & Jia, Ning & Qu, Xiaobo & He, Zhengbing, 2023. "Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part I: Route-dependent attraction and its modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
  109. Faguang Wen & Jiming Jiang & Yihui Luan, 2024. "Model Selection Path and Construction of Model Confidence Set under High-Dimensional Variables," Mathematics, MDPI, vol. 12(5), pages 1-21, February.
  110. José Luis Montiel Olea & Pietro Ortoleva & Mallesh Pai & Andrea Prat, 2021. "Competing Models," Working Papers 2021-89, Princeton University. Economics Department..
  111. Jose Luis Montiel Olea & Pietro Ortoleva & Mallesh M Pai & Andrea Prat, 2019. "Competing Models," Papers 1907.03809, arXiv.org, revised Nov 2021.
  112. Fletcher, David & Dillingham, Peter W., 2011. "Model-averaged confidence intervals for factorial experiments," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 3041-3048, November.
  113. A. Mohammadi & M. Salehi-Rad & E. Wit, 2013. "Using mixture of Gamma distributions for Bayesian analysis in an M/G/1 queue with optional second service," Computational Statistics, Springer, vol. 28(2), pages 683-700, April.
  114. Enrique Moral-Benito, 2010. "Model Averaging in Economics," Working Papers wp2010_1008, CEMFI.
  115. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric model averaging of ultra-high dimensional time series," CeMMAP working papers CWP62/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  116. García-Magariños Manuel & Egeland Thore & López-de-Ullibarri Ignacio & Hjort Nils L. & Salas Antonio, 2015. "A parametric approach to kinship hypothesis testing using identity-by-descent parameters," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(5), pages 465-479, November.
  117. Hee-Young Kim & Christian H. Weiß & Tobias A. Möller, 2020. "Models for autoregressive processes of bounded counts: How different are they?," Computational Statistics, Springer, vol. 35(4), pages 1715-1736, December.
  118. Y. Chebud & A. Melesse, 2012. "Spatiotemporal Surface-Groundwater Interaction Simulation in South Florida," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(15), pages 4449-4466, December.
  119. David R. Bickel, 2013. "Minimax-Optimal Strength of Statistical Evidence for a Composite Alternative Hypothesis," International Statistical Review, International Statistical Institute, vol. 81(2), pages 188-206, August.
  120. S. C. Pandhare & T. V. Ramanathan, 2020. "The robust focused information criterion for strong mixing stochastic processes with $$\mathscr {L}^{2}$$ L 2 -differentiable parametric densities," Statistical Inference for Stochastic Processes, Springer, vol. 23(3), pages 637-663, October.
  121. Egil Ferkingstad & Anders L{o}land & Mathilde Wilhelmsen, 2011. "Causal modeling and inference for electricity markets," Papers 1110.5429, arXiv.org.
  122. van den Brakel Jan A. & Buelens Bart, 2015. "Covariate Selection for Small Area Estimation in Repeated Sample Surveys," Statistics in Transition New Series, Statistics Poland, vol. 16(4), pages 523-540, December.
  123. Heyard, Rachel & Held, Leonhard, 2019. "The quantile probability model," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 84-99.
  124. Gildas Mazo & François Portier, 2021. "Parametric versus nonparametric: The fitness coefficient," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1344-1383, December.
  125. Bastien Marquis & Maarten Jansen, 2022. "Information criteria bias correction for group selection," Statistical Papers, Springer, vol. 63(5), pages 1387-1414, October.
  126. Ørnulf Borgan & Ingrid K. Glad, 2024. "A conversation with Nils Lid Hjort," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(3), pages 914-935, September.
  127. Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
  128. Vahid Nassiri & Ignace Loris, 2014. "An efficient algorithm for structured sparse quantile regression," Computational Statistics, Springer, vol. 29(5), pages 1321-1343, October.
  129. 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.
  130. Philippe Van Kerm & Seunghee Yu & Chung Choe, 2016. "Decomposing quantile wage gaps: a conditional likelihood approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 507-527, August.
  131. Martin Jullum & Nils Lid Hjort, 2019. "What price semiparametric Cox regression?," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 406-438, July.
  132. Liu, Chu-An, 2015. "Distribution theory of the least squares averaging estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 142-159.
  133. Ando, Tomohiro & Tsay, Ruey, 2010. "Predictive likelihood for Bayesian model selection and averaging," International Journal of Forecasting, Elsevier, vol. 26(4), pages 744-763, October.
  134. Sourav Medya & Mohammad Rasoolinejad & Yang Yang & Brian Uzzi, 2022. "An Exploratory Study of Stock Price Movements from Earnings Calls," Papers 2203.12460, arXiv.org.
  135. Ingrid Dæhlen & Nils Lid Hjort & Ingrid Hobæk Haff, 2024. "Accurate bias estimation with applications to focused model selection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(2), pages 724-759, June.
  136. Button Patrick, 2016. "Model Uncertainty and Model Averaging in Regression Discontinuity Designs," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 103-116, January.
  137. Thomas Fung & Joanna J.J. Wang & Eugene Seneta, 2014. "The Deviance Information Criterion in Comparison of Normal Mixing Models," International Statistical Review, International Statistical Institute, vol. 82(3), pages 411-421, December.
  138. Ji Ryoo, 2012. "G. FITZMAURICE, M. DAVIDIAN, G. VERBEKE & G. MOLENBERGHS (eds) (2008) Longitudinal Data Analysis: A Handbook of Modern Statistical Methods," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 423-424, April.
  139. Romain Duval & Davide Furceri & Jakob Miethe, 2021. "Robust political economy correlates of major product and labor market reforms in advanced economies: Evidence from BAMLE for logit models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 98-124, January.
  140. Kristoffer H. Hellton, 2023. "Penalized angular regression for personalized predictions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 184-212, March.
  141. Emiliano, Paulo C. & Vivanco, Mário J.F. & de Menezes, Fortunato S., 2014. "Information criteria: How do they behave in different models?," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 141-153.
  142. Claudio, Morana, 2015. "Model Averaging by Stacking," Working Papers 310, University of Milano-Bicocca, Department of Economics, revised 29 Oct 2015.
  143. Ryan Greenaway-McGrevy & Kade Sorensen, 2021. "A spatial model averaging approach to measuring house prices," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-32, December.
  144. VAN KERM Philippe & YU Seunghee & CHOE Chung, 2014. "Wage differentials between native, immigrant and cross-border workers: Evidence and model comparisons," LISER Working Paper Series 2014-05, Luxembourg Institute of Socio-Economic Research (LISER).
  145. Mora-Valencia, Andrés & Rodríguez-Raga, Santiago & Vanegas, Esteban, 2021. "Skew index: Descriptive analysis, predictive power, and short-term forecast," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
  146. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
  147. De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2022. "Sampling properties of the Bayesian posterior mean with an application to WALS estimation," Journal of Econometrics, Elsevier, vol. 230(2), pages 299-317.
  148. Tuan Tri Ngo & Huy Van Nguyen & Thanh Hai Pham & Tien Van Nguyen & Kien Duy Vu & Minh Duc Pham & Dung Phung & Anh Ngoc Thi Tran & Phuong The Nguyen & Phuong Mai Le & An Minh Thi Dao & Hiep Tri Ngo & M, 2022. "The relationship between team dynamics with healthcare coordination and clinical work satisfaction among Commune Health Workers: A Bayesian model averaging study," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(5), pages 2684-2696, September.
  149. Alice X. D. Dong & Jennifer S. K. Chan & Gareth W. Peters, 2014. "Risk Margin Quantile Function Via Parametric and Non-Parametric Bayesian Quantile Regression," Papers 1402.2492, arXiv.org.
  150. Peng Zeng & Qinqin Hu & Xiaoyu Li, 2017. "Geometry and Degrees of Freedom of Linearly Constrained Generalized Lasso," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 989-1008, December.
  151. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2016. "Generalized Least Squares Model Averaging," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1692-1752, December.
  152. Meng Li & Sijia Xiang & Weixin Yao, 2016. "Robust estimation of the number of components for mixtures of linear regression models," Computational Statistics, Springer, vol. 31(4), pages 1539-1555, December.
  153. Emilian Dobrescu, 2015. "Net Indirect Taxes and Sectoral Structure of Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-29, June.
  154. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
  155. Gioldasis, Georgios & Musolesi, Antonio & Simioni, Michel, 2023. "Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection," International Journal of Forecasting, Elsevier, vol. 39(1), pages 144-169.
  156. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
  157. Yang Feng & Qingfeng Liu, 2020. "Nested Model Averaging on Solution Path for High-dimensional Linear Regression," Papers 2005.08057, arXiv.org.
  158. Miguel A. Negrín & Julian Nam & Andrew H. Briggs, 2017. "Bayesian Solutions for Handling Uncertainty in Survival Extrapolation," Medical Decision Making, , vol. 37(4), pages 367-376, May.
  159. Matthew W. Wheeler & Todd Blessinger & Kan Shao & Bruce C. Allen & Louis Olszyk & J. Allen Davis & Jeffrey S Gift, 2020. "Quantitative Risk Assessment: Developing a Bayesian Approach to Dichotomous Dose–Response Uncertainty," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1706-1722, September.
  160. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers 61/13, Institute for Fiscal Studies.
  161. Giuseppe De Luca & Jan Magnus & Franco Peracchi, 2022. "Asymptotic properties of the weighted average least squares (WALS) estimator," Tinbergen Institute Discussion Papers 22-022/III, Tinbergen Institute.
  162. Seya, Hajime & Yamagata, Yoshiki & Tsutsumi, Morito, 2013. "Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 429-444.
  163. Steen MAGNUSSEN, 2018. "An estimation strategy to protect against over-estimating precision in a LiDAR-based prediction of a stand mean," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 64(12), pages 497-505.
  164. Alessandro Casa & Luca Scrucca & Giovanna Menardi, 2021. "Better than the best? Answers via model ensemble in density-based clustering," 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 599-623, September.
  165. Zhongqi Liang & Qihua Wang & Yuting Wei, 2022. "Robust model selection with covariables missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(3), pages 539-557, June.
  166. Bum Chul Kwon & Vibha Anand & Peter Achenbach & Jessica L. Dunne & William Hagopian & Jianying Hu & Eileen Koski & Åke Lernmark & Markus Lundgren & Kenney Ng & Jorma Toppari & Riitta Veijola & Brigitt, 2022. "Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  167. David Mazáček & Jiří Panoš, 2022. "Key determinants of new residential real estate prices in Prague," FFA Working Papers 5.002, Prague University of Economics and Business, revised 11 Apr 2023.
  168. Dirick, Lore & Claeskens, Gerda & Vasnev, Andrey & Baesens, Bart, 2022. "A hierarchical mixture cure model with unobserved heterogeneity for credit risk," Econometrics and Statistics, Elsevier, vol. 22(C), pages 39-55.
  169. Messner, Wolfgang, 2024. "Distance is the spice, but not the whole enchilada: Country-pair psychic distance stimuli and country fixed effects in a deep learning implementation of the trade flow model," International Business Review, Elsevier, vol. 33(1).
  170. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2023. "Optimal Local Model Averaging for Divergent-Dimensional Functional-Coefficient Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202309, University of Kansas, Department of Economics, revised Sep 2023.
  171. Chen, Tianyi & Wong, Yiik Diew & Shi, Xiupeng & Wang, Xueqin, 2022. "Optimized structure learning of Bayesian Network for investigating causation of vehicles’ on-road crashes," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
  172. Yonekura, Shouto & Beskos, Alexandros & Singh, Sumeetpal S., 2021. "Asymptotic analysis of model selection criteria for general hidden Markov models," Stochastic Processes and their Applications, Elsevier, vol. 132(C), pages 164-191.
  173. HAEDO, Christian & MOUCHART , Michel & ,, 2013. "Specialized agglomerations with areal data: model and detection," LIDAM Discussion Papers CORE 2013060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  174. Xiaohui Liu & Yuanyuan Li & Jiming Jiang, 2021. "Simple measures of uncertainty for model selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 673-692, September.
  175. Feng, Yang & Liu, Qingfeng & Okui, Ryo, 2020. "On the sparsity of Mallows model averaging estimator," Economics Letters, Elsevier, vol. 187(C).
  176. Deng, Jian, 2022. "Probabilistic characterization of soil properties based on the maximum entropy method from fractional moments: Model development, case study, and application," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  177. Su, Jiun-Hua, 2021. "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, vol. 223(1), pages 96-124.
  178. Rachel S. McCrea & Byron J. T. Morgan, 2011. "Multistate Mark–Recapture Model Selection Using Score Tests," Biometrics, The International Biometric Society, vol. 67(1), pages 234-241, March.
  179. Anwen Yin, 2024. "Predictive model averaging with parameter instability and heteroskedasticity," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 418-442, April.
  180. Yuting Wei & Qihua Wang & Wei Liu, 2021. "Model averaging for linear models with responses missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 535-553, June.
  181. Ko, Vinnie & Hjort, Nils Lid, 2019. "Copula information criterion for model selection with two-stage maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 12(C), pages 167-180.
  182. Haiying Wang & Yang Li & Jianguo Sun, 2015. "Focused and Model Average Estimation for Regression Analysis of Panel Count Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 732-745, September.
  183. Georg Gutjahr & Björn Bornkamp, 2017. "Likelihood ratio tests for a dose-response effect using multiple nonlinear regression models," Biometrics, The International Biometric Society, vol. 73(1), pages 197-205, March.
  184. Spanos, Aris, 2010. "Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification," Journal of Econometrics, Elsevier, vol. 158(2), pages 204-220, October.
  185. Shahid Latif & Slobodan P. Simonovic, 2022. "Nonparametric Approach to Copula Estimation in Compounding The Joint Impact of Storm Surge and Rainfall Events in Coastal Flood Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5599-5632, November.
  186. Bart Buelens & Jan A. van den Brakel, 2015. "Covariate selection for small area estimation in repeated sample surveys," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(4), pages 523-540, December.
  187. Edsel A. Peña & Wensong Wu & Walter Piegorsch & Ronald W. West & LingLing An, 2017. "Model Selection and Estimation with Quantal‐Response Data in Benchmark Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 716-732, April.
  188. Mathias Drton & Martyn Plummer, 2017. "A Bayesian information criterion for singular models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 323-380, March.
  189. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
  190. Jin‐Hua Chen & Chun‐Shu Chen & Meng‐Fan Huang & Hung‐Chih Lin, 2016. "Estimating the Probability of Rare Events Occurring Using a Local Model Averaging," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1855-1870, October.
  191. Jardet, Caroline & Monfort, Alain & Pegoraro, Fulvio, 2013. "No-arbitrage Near-Cointegrated VAR(p) term structure models, term premia and GDP growth," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 389-402.
  192. Saraev, Vadim & Valatin, Gregory & Peace, Andrew & Quine, Christopher, 2019. "How does a biodiversity value impact upon optimal rotation length? An investigation using species richness and forest stand age," Forest Policy and Economics, Elsevier, vol. 107(C), pages 1-1.
  193. Gerda Claeskens & Fabrizio Consentino, 2008. "Variable Selection with Incomplete Covariate Data," Biometrics, The International Biometric Society, vol. 64(4), pages 1062-1069, December.
  194. Jing Zhou & Gerda Claeskens & Jelena Bradic, 2020. "Detangling robustness in high dimensions: composite versus model-averaged estimation," Papers 2006.07457, arXiv.org.
  195. Zhang, Xinyu & Wan, Alan T.K. & Zou, Guohua, 2013. "Model averaging by jackknife criterion in models with dependent data," Journal of Econometrics, Elsevier, vol. 174(2), pages 82-94.
  196. Stefan Sperlich, 2013. "Comments on: Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 227-233, June.
  197. Masataka Taguri & Yutaka Matsuyama & Yasuo Ohashi, 2014. "Model selection criterion for causal parameters in structural mean models based on a quasi-likelihood," Biometrics, The International Biometric Society, vol. 70(3), pages 721-730, September.
  198. Jaroslava Hlouskova & Martin Wagner, 2013. "The Determinants of Long-Run Economic Growth: A Conceptually and Computationally Simple Approach," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 445-492, December.
  199. Steffen Grønneberg & Jonas Moss & Njål Foldnes, 2020. "Partial Identification of Latent Correlations with Binary Data," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 1028-1051, December.
  200. Wudi Wei & Junjun Jiang & Hao Liang & Lian Gao & Bingyu Liang & Jiegang Huang & Ning Zang & Yanyan Liao & Jun Yu & Jingzhen Lai & Fengxiang Qin & Jinming Su & Li Ye & Hui Chen, 2016. "Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-13, June.
  201. Cornelius Fritz & Michael Lebacher & Göran Kauermann, 2020. "Tempus volat, hora fugit: A survey of tie‐oriented dynamic network models in discrete and continuous time," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 275-299, August.
  202. Heiler, Phillip & Mareckova, Jana, 2021. "Shrinkage for categorical regressors," Journal of Econometrics, Elsevier, vol. 223(1), pages 161-189.
  203. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
  204. Christian Brownlees & Vladislav Morozov, 2022. "Unit Averaging for Heterogeneous Panels," Papers 2210.14205, arXiv.org, revised May 2024.
  205. Ko, Vinnie & Hjort, Nils Lid, 2019. "Model robust inference with two-stage maximum likelihood estimation for copulas," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 362-381.
  206. Mikrajuddin Abdullah, 2024. "Theoretical Foundation for the Pareto Distribution of International Trade Strength and Introduction of an Equation for International Trade Forecasting," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 52(1), pages 17-29, March.
  207. Yong Li & Zhou Wu & Jun Yu & Tao Zeng, 2024. "A Note on AIC and TIC for Model Selection," Working Papers 202420, University of Macau, Faculty of Business Administration.
  208. Ghosh, D. & Yuan, Z., 2009. "An improved model averaging scheme for logistic regression," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1670-1681, September.
  209. Zhang, Qingzhao & Duan, Xiaogang & Ma, Shuangge, 2017. "Focused information criterion and model averaging with generalized rank regression," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 11-19.
  210. Funovits, Bernd, 2024. "Identifiability and estimation of possibly non-invertible SVARMA Models: The normalised canonical WHF parametrisation," Journal of Econometrics, Elsevier, vol. 241(2).
  211. Ferrari, Davide & Zheng, Chao, 2016. "Reliable inference for complex models by discriminative composite likelihood estimation," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 68-80.
  212. Mr. Jorge A Chan-Lau, 2017. "Lasso Regressions and Forecasting Models in Applied Stress Testing," IMF Working Papers 2017/108, International Monetary Fund.
  213. Wagner, Martin & Hlouskova, Jaroslava, 2009. "Growth Regressions, Principal Components and Frequentist Model Averaging," Economics Series 236, Institute for Advanced Studies.
  214. Liu, Chu-An, 2018. "Averaging estimators for kernel regressions," Economics Letters, Elsevier, vol. 171(C), pages 102-105.
  215. Turek, Daniel & Fletcher, David, 2012. "Model-averaged Wald confidence intervals," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2809-2815.
  216. Yehua Li & Naisyin Wang & Raymond J. Carroll, 2013. "Selecting the Number of Principal Components in Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1284-1294, December.
  217. Powell, Siobhan & Vianna Cezar, Gustavo & Apostolaki-Iosifidou, Elpiniki & Rajagopal, Ram, 2022. "Large-scale scenarios of electric vehicle charging with a data-driven model of control," Energy, Elsevier, vol. 248(C).
  218. Edvard Bakhitov, 2020. "Frequentist Shrinkage under Inequality Constraints," Papers 2001.10586, arXiv.org.
  219. Schomaker Michael & Heumann Christian, 2011. "Model Averaging in Factor Analysis: An Analysis of Olympic Decathlon Data," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(1), pages 1-15, January.
  220. Fiaschi, Davide & Gianmoena, Lisa & Parenti, Angela, 2018. "Spatial club dynamics in European regions," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 115-130.
  221. Magnus, Jan R. & Wan, Alan T.K. & Zhang, Xinyu, 2011. "Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1331-1341, March.
  222. Emil Aas Stoltenberg & Nils Lid Hjort, 2021. "Models and inference for on–off data via clipped Ornstein–Uhlenbeck processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(3), pages 908-929, September.
  223. Riet Bork & Raoul P. P. P. Grasman & Lourens J. Waldorp, 2018. "Unidimensional factor models imply weaker partial correlations than zero-order correlations," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 443-452, June.
  224. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
  225. Céline Cunen & Nils Lid Hjort, 2020. "Confidence Distributions for FIC Scores," Econometrics, MDPI, vol. 8(3), pages 1-28, July.
  226. Jun Yu & HaiYing Wang, 2022. "Subdata selection algorithm for linear model discrimination," Statistical Papers, Springer, vol. 63(6), pages 1883-1906, December.
  227. Lobna ABID & Soukeina Zaghdene & Afif Masmoudi & Sonia Zouari Ghorbel, 2017. "Bayesian Network Modeling: A Case Study of Credit Scoring Analysis of Consumer Loans Default Payment," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 7(9), pages 846-857, September.
  228. Ursula S. Goth & Hugo L. Hammer & Bjørgulf Claussen, 2014. "Utilization of Norway’s Emergency Wards: The Second 5 Years after the Introduction of the Patient List System," IJERPH, MDPI, vol. 11(3), pages 1-12, March.
  229. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.
  230. Yan Li & Partha Lahiri, 2019. "A Simple Adaptation of Variable Selection Software for Regression Models to Select Variables in Nested Error Regression Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 302-317, December.
  231. Boot, Tom, 2023. "Joint inference based on Stein-type averaging estimators in the linear regression model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1542-1563.
  232. 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.
  233. Subramanian, Sundarraman, 2016. "Bootstrap likelihood ratio confidence bands for survival functions under random censorship and its semiparametric extension," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 58-81.
  234. Matloff, Norman, 2016. "Software Alchemy: Turning Complex Statistical Computations into Embarrassingly-Parallel Ones," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 71(i04).
  235. den Boer, Arnoud V. & Sierag, Dirk D., 2021. "Decision-based model selection," European Journal of Operational Research, Elsevier, vol. 290(2), pages 671-686.
  236. Tumala, Mohammed M & Olubusoye, Olusanya E & Yaaba, Baba N & Yaya, OlaOluwa S & Akanbi, Olawale B, 2017. "Forecasting Nigerian Inflation using Model Averaging methods: Modelling Frameworks to Central Banks," MPRA Paper 88754, University Library of Munich, Germany, revised Feb 2018.
  237. Jan Lohmeyer & Franz Palm & Jean‐Pierre Urbain, 2024. "Consistency of averaged impulse response estimators in vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 691-713, September.
  238. Feng, Haoyuan & Liu, Yue & Wu, Jie & Guo, Kun, 2023. "Financial market spillovers and macroeconomic shocks: Evidence from China," Research in International Business and Finance, Elsevier, vol. 65(C).
  239. Kira Alhorn & Holger Dette & Kirsten Schorning, 2021. "Optimal Designs for Model Averaging in non-nested Models," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 745-778, August.
  240. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
  241. Zhongqi Liang & Qihua Wang, 2023. "A robust model averaging approach for partially linear models with responses missing at random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(4), pages 1933-1952, December.
  242. Lasanthi C. R. Pelawa Watagoda & David J. Olive, 2021. "Bootstrapping multiple linear regression after variable selection," Statistical Papers, Springer, vol. 62(2), pages 681-700, April.
  243. Judith Anne Clarke, 2017. "Model Averaging OLS and 2SLS: An Application of the WALS Procedure," Econometrics Working Papers 1701, Department of Economics, University of Victoria.
  244. Rina Wu & Jiquan Zhang & Yuhai Bao & Enliang Guo, 2019. "Run Theory and Copula-Based Drought Risk Analysis for Songnen Grassland in Northeastern China," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
  245. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.
  246. David J Albers & Matthew Levine & Bruce Gluckman & Henry Ginsberg & George Hripcsak & Lena Mamykina, 2017. "Personalized glucose forecasting for type 2 diabetes using data assimilation," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-38, April.
  247. Zhang, Qi & Tong, Tingting & Wu, Shunyao, 2020. "Hybrid link prediction via model averaging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
  248. Mathieu Gatumel & Florian Ielpo, 2014. "Commodity Markets through the business cycle," Post-Print hal-01302479, HAL.
  249. Dennis M. Feehan, 2018. "Separating the Signal From the Noise: Evidence for Deceleration in Old-Age Death Rates," Demography, Springer;Population Association of America (PAA), vol. 55(6), pages 2025-2044, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.