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A Primer on Copulas for Count Data

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Cited by:

  1. Partha Deb & Pravin K. Trivedi & David M. Zimmer, 2014. "Cost‐Offsets Of Prescription Drug Expenditures: Data Analysis Via A Copula‐Based Bivariate Dynamic Hurdle Model," Health Economics, John Wiley & Sons, Ltd., vol. 23(10), pages 1242-1259, October.
  2. Adelchi Azzalini & Marc G. Genton, 2015. "Discussion," International Statistical Review, International Statistical Institute, vol. 83(2), pages 198-202, August.
  3. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," Economic Research Papers 270232, University of Warwick - Department of Economics.
  4. Shi, Peng & Valdez, Emiliano A., 2014. "Multivariate negative binomial models for insurance claim counts," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 18-29.
  5. Emura, Takeshi & Wang, Weijing, 2012. "Nonparametric maximum likelihood estimation for dependent truncation data based on copulas," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 171-188.
  6. Marra, Giampiero & Wyszynski, Karol, 2016. "Semi-parametric copula sample selection models for count responses," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 110-129.
  7. Jean-François Plante, 2017. "Rank correlation under categorical confounding," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-19, December.
  8. Karol Wyszynski & Giampiero Marra, 2018. "Sample selection models for count data in R," Computational Statistics, Springer, vol. 33(3), pages 1385-1412, September.
  9. Edward W. Frees & Gee Lee & Lu Yang, 2016. "Multivariate Frequency-Severity Regression Models in Insurance," Risks, MDPI, vol. 4(1), pages 1-36, February.
  10. Mai Jan-Frederik & Scherer Matthias, 2013. "What makes dependence modeling challenging? Pitfalls and ways to circumvent them," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 287-306, December.
  11. Kimberly F. Sellers & Tong Li & Yixuan Wu & Narayanaswamy Balakrishnan, 2021. "A Flexible Multivariate Distribution for Correlated Count Data," Stats, MDPI, vol. 4(2), pages 1-19, April.
  12. Dutang, C. & Lefèvre, C. & Loisel, S., 2013. "On an asymptotic rule A+B/u for ultimate ruin probabilities under dependence by mixing," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 774-785.
  13. Cossette, Hélène & Marceau, Etienne & Perreault, Samuel, 2015. "On two families of bivariate distributions with exponential marginals: Aggregation and capital allocation," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 214-224.
  14. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, vol. 5(1), pages 1-11, February.
  15. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
  16. Kobus, Martyna & Kurek, Radosław, 2018. "Copula-based measurement of interdependence for discrete distributions," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 27-39.
  17. Pinto Da Costa, Joaquim & Roque, Luís A.C. & Soares, Carlos, 2015. "The weighted rank correlation coefficient rW2 in the case of ties," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 20-26.
  18. Martyna Kobus & Radosław Kurek, 2019. "Multidimensional polarization for ordinal data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(3), pages 301-317, September.
  19. Balkema, A.A. & Embrechts, P. & Nolde, N., 2010. "Meta densities and the shape of their sample clouds," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1738-1754, August.
  20. M. Mesfioui & T. Bouezmarni & M. Belalia, 2023. "Copula-based link functions in binary regression models," Statistical Papers, Springer, vol. 64(2), pages 557-585, April.
  21. Lu Yang & Claudia Czado, 2022. "Two‐part D‐vine copula models for longitudinal insurance claim data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1534-1561, December.
  22. Kolev, Nikolai, 2016. "Characterizations of the class of bivariate Gompertz distributions," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 173-179.
  23. Veraart, Almut E.D., 2019. "Modeling, simulation and inference for multivariate time series of counts using trawl processes," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 110-129.
  24. Michel Denuit & Yang Lu, 2021. "Wishart‐gamma random effects models with applications to nonlife insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(2), pages 443-481, June.
  25. Genest Christian & Scherer Matthias, 2020. "Insurance applications of dependence modeling: An interview with Edward (Jed) Frees," Dependence Modeling, De Gruyter, vol. 8(1), pages 93-106, January.
  26. Dmitriy Borzykh & Henry Penikas, 2021. "IRB PD model accuracy validation in the presence of default correlation: a twin confidence interval approach," Risk Management, Palgrave Macmillan, vol. 23(4), pages 282-300, December.
  27. Lluís Bermúdez & Dimitris Karlis, 2022. "Copula-based bivariate finite mixture regression models with an application for insurance claim count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1082-1099, December.
  28. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
  29. Krupskii, Pavel & Genton, Marc G., 2019. "A copula model for non-Gaussian multivariate spatial data," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 264-277.
  30. Gery Geenens, 2024. "(Re-)Reading Sklar (1959)—A Personal View on Sklar’s Theorem," Mathematics, MDPI, vol. 12(3), pages 1-7, January.
  31. Moatafa Allameh Zadeh, 2020. "Seismic Nowcasting Using Shannon Information Entropy with Copula Models and Artificial Neural Networks," Current Trends On Biostatistics & Biometrics, Lupine Publishers, LLC, vol. 3(2), pages 325-333, August.
  32. Iryna Kyzyma & Alessio Fusco & Philippe Van Kerm, 2022. "Distributional Change: Assessing the Contribution of Household Income Sources," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 158-184, February.
  33. Genest, Christian & Nešlehová, Johanna G. & Rémillard, Bruno, 2013. "On the estimation of Spearman’s rho and related tests of independence for possibly discontinuous multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 214-228.
  34. Longla, Martial & Peligrad, Magda, 2012. "Some aspects of modeling dependence in copula-based Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 234-240.
  35. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
  36. Mothafer, Ghasak I.M.A. & Yamamoto, Toshiyuki & Shankar, Venkataraman N., 2018. "A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 84-105.
  37. Mauro Laudicella & Paolo Li Donni, 2022. "The dynamic interdependence in the demand of primary and emergency secondary care: A hidden Markov approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 521-536, April.
  38. Segers, Johan & Sibuya, Masaaki & Tsukahara, Hideatsu, 2017. "The empirical beta copula," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 35-51.
  39. Genest, Christian & Nešlehová, Johanna G. & Rémillard, Bruno, 2017. "Asymptotic behavior of the empirical multilinear copula process under broad conditions," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 82-110.
  40. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
  41. De Backer, Mickael & El Ghouch, Anouar & Van Keilegom, Ingrid, 2016. "Semiparametric Copula Quantile Regression for Complete or Censored Data," LIDAM Discussion Papers ISBA 2016009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  42. Tzougas, George & Pignatelli di Cerchiara, Alice, 2021. "The multivariate mixed Negative Binomial regression model with an application to insurance a posteriori ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 602-625.
  43. Johny Pambabay-Calero & Sergio Bauz-Olvera & Ana Nieto-Librero & Ana Sánchez-García & Puri Galindo-Villardón, 2021. "Hierarchical Modeling for Diagnostic Test Accuracy Using Multivariate Probability Distribution Functions," Mathematics, MDPI, vol. 9(11), pages 1-20, June.
  44. Wei, Zheng & Kim, Daeyoung, 2021. "Measure of asymmetric association for ordinal contingency tables via the bilinear extension copula," Statistics & Probability Letters, Elsevier, vol. 178(C).
  45. Fantazzini, Dean, 2020. "Discussing copulas with Sergey Aivazian: a memoir," MPRA Paper 102317, University Library of Munich, Germany.
  46. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
  47. Marceau, Etienne, 2009. "On the discrete-time compound renewal risk model with dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 245-259, April.
  48. Naumzik, Christof & Feuerriegel, Stefan & Nielsen, Anne Molgaard, 2023. "Data-driven dynamic treatment planning for chronic diseases," European Journal of Operational Research, Elsevier, vol. 305(2), pages 853-867.
  49. Faugeras Olivier P., 2017. "Inference for copula modeling of discrete data: a cautionary tale and some facts," Dependence Modeling, De Gruyter, vol. 5(1), pages 121-132, January.
  50. Aristidis Nikoloulopoulos & Dimitris Karlis, 2010. "Regression in a copula model for bivariate count data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1555-1568.
  51. Durante Fabrizio & Puccetti Giovanni & Scherer Matthias & Vanduffel Steven, 2016. "Stat Trek," Dependence Modeling, De Gruyter, vol. 4(1), pages 109-122, May.
  52. Bochao Jia & Suwa Xu & Guanghua Xiao & Vishal Lamba & Faming Liang, 2017. "Learning gene regulatory networks from next generation sequencing data," Biometrics, The International Biometric Society, vol. 73(4), pages 1221-1230, December.
  53. Martyna Kobus & Radoslaw Kurek, 2017. "Copula-based measurement of interdependence for discrete distributions," Working Papers 431, ECINEQ, Society for the Study of Economic Inequality.
  54. Stöber, Jakob & Hong, Hyokyoung Grace & Czado, Claudia & Ghosh, Pulak, 2015. "Comorbidity of chronic diseases in the elderly: Patterns identified by a copula design for mixed responses," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 28-39.
  55. Baker, Rose, 2008. "An order-statistics-based method for constructing multivariate distributions with fixed marginals," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2312-2327, November.
  56. Mathews Joseph & Bhattacharya Sumangal & Das Ishapathik & Sen Sumen, 2022. "Multiple inflated negative binomial regression for correlated multivariate count data," Dependence Modeling, De Gruyter, vol. 10(1), pages 290-307, January.
  57. Mesfioui, Mhamed & Quessy, Jean-François, 2010. "Concordance measures for multivariate non-continuous random vectors," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2398-2410, November.
  58. Cheung, Ka Chun, 2009. "Upper comonotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 35-40, August.
  59. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
  60. Tzougas, George & Makariou, Despoina, 2022. "The multivariate Poisson-Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," LSE Research Online Documents on Economics 117197, London School of Economics and Political Science, LSE Library.
  61. Jack Britton & Neil Shephard & Laura van der Erve, 2019. "Econometrics of valuing income contingent student loans using administrative data: groups of English students," IFS Working Papers W19/04, Institute for Fiscal Studies.
  62. repec:hal:wpaper:hal-00746251 is not listed on IDEAS
  63. Elizabeth D. Schifano & Himchan Jeong & Ved Deshpande & Dipak K. Dey, 2021. "Fully and empirical Bayes approaches to estimating copula-based models for bivariate mixed outcomes using Hamiltonian Monte Carlo," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 133-152, March.
  64. Craiu, V. Radu & Sabeti, Avideh, 2012. "In mixed company: Bayesian inference for bivariate conditional copula models with discrete and continuous outcomes," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 106-120.
  65. Nagler, Thomas, 2018. "A generic approach to nonparametric function estimation with mixed data," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 326-330.
  66. Marbac, Matthieu & Sedki, Mohammed, 2017. "A family of block-wise one-factor distributions for modeling high-dimensional binary data," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 130-145.
  67. Giampiero Marra & Rosalba Radice & David Zimmer, 2021. "Did the ACA's “guaranteed issue” provision cause adverse selection into nongroup insurance? Analysis using a copula‐based hurdle model," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 2246-2263, September.
  68. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
  69. J. A. Carrillo & M. Nieto & J. F. Velez & D. Velez, 2021. "A New Machine Learning Forecasting Algorithm Based on Bivariate Copula Functions," Forecasting, MDPI, vol. 3(2), pages 1-22, May.
  70. Geenens Gery, 2020. "Copula modeling for discrete random vectors," Dependence Modeling, De Gruyter, vol. 8(1), pages 417-440, January.
  71. Qi Liu & Chun Li & Valentine Wanga & Bryan E. Shepherd, 2018. "Covariate†adjusted Spearman's rank correlation with probability†scale residuals," Biometrics, The International Biometric Society, vol. 74(2), pages 595-605, June.
  72. Jae-Kyung Woo & Haibo Liu, 2018. "Discounted Aggregate Claim Costs Until Ruin in the Discrete-Time Renewal Risk Model," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1285-1318, December.
  73. Marchese, Scott & Diao, Guoqing, 2017. "Density ratio model for multivariate outcomes," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 249-261.
  74. Zilko, Aurelius A. & Kurowicka, Dorota, 2016. "Copula in a multivariate mixed discrete–continuous model," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 28-55.
  75. Faugeras, Olivier P., 2013. "Sklar’s theorem derived using probabilistic continuation and two consistency results," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 271-277.
  76. Paul Embrechts, 2009. "Copulas: A Personal View," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 639-650, September.
  77. Gunawardana, Asanka & Konietschke, Frank, 2019. "Nonparametric multiple contrast tests for general multivariate factorial designs," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 165-180.
  78. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
  79. Kasa, Siva Rajesh & Rajan, Vaibhav, 2022. "Improved Inference of Gaussian Mixture Copula Model for Clustering and Reproducibility Analysis using Automatic Differentiation," Econometrics and Statistics, Elsevier, vol. 22(C), pages 67-97.
  80. Xiaotian Zheng & Athanasios Kottas & Bruno Sansó, 2023. "Bayesian geostatistical modeling for discrete‐valued processes," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.
  81. George Tzougas & Despoina Makariou, 2022. "The multivariate Poisson‐Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(4), pages 401-417, December.
  82. 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).
  83. Tobias Fissler & Marc-Oliver Pohle, 2023. "Generalised Covariances and Correlations," Papers 2307.03594, arXiv.org, revised Sep 2023.
  84. Geenens Gery, 2020. "Copula modeling for discrete random vectors," Dependence Modeling, De Gruyter, vol. 8(1), pages 417-440, January.
  85. Jonas Moss & Steffen Grønneberg, 2023. "Partial Identification of Latent Correlations with Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 241-252, March.
  86. Kojadinovic, Ivan, 2017. "Some copula inference procedures adapted to the presence of ties," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 24-41.
  87. Genest Christian & Scherer Matthias, 2020. "Insurance applications of dependence modeling: An interview with Edward (Jed) Frees," Dependence Modeling, De Gruyter, vol. 8(1), pages 93-106, January.
  88. Kojadinovic, Ivan & Stemikovskaya, Kristina, 2019. "Subsampling (weighted smooth) empirical copula processes," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 704-723.
  89. Mamode Khan Naushad & Rumjaun Wasseem & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Computing with bivariate COM-Poisson model under different copulas," Monte Carlo Methods and Applications, De Gruyter, vol. 23(2), pages 131-146, June.
  90. Romera, Rosario & Molanes, Elisa M., 2008. "Copulas in finance and insurance," DES - Working Papers. Statistics and Econometrics. WS ws086321, Universidad Carlos III de Madrid. Departamento de Estadística.
  91. Emura, Takeshi & Lai, Ching-Chieh & Sun, Li-Hsien, 2023. "Change point estimation under a copula-based Markov chain model for binomial time series," Econometrics and Statistics, Elsevier, vol. 28(C), pages 120-137.
  92. Serge B. Provost & Yishan Zang, 2024. "Nonparametric Copula Density Estimation Methodologies," Mathematics, MDPI, vol. 12(3), pages 1-35, January.
  93. L. L. Henn, 2022. "Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data," Computational Statistics, Springer, vol. 37(2), pages 909-946, April.
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  96. Manuela Schreyer & Roland Paulin & Wolfgang Trutschnig, 2017. "On the exact region determined by Kendall's τ and Spearman's ρ," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 613-633, March.
  97. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
  98. Marchese, Scott & Diao, Guoqing, 2018. "Joint regression analysis of mixed-type outcome data via efficient scores," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 156-170.
  99. Gao, Guangyuan & Li, Jiahong, 2023. "Dependence modeling of frequency-severity of insurance claims using waiting time," Insurance: Mathematics and Economics, Elsevier, vol. 109(C), pages 29-51.
  100. Panagiotelis, Anastasios & Czado, Claudia & Joe, Harry & Stöber, Jakob, 2017. "Model selection for discrete regular vine copulas," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 138-152.
  101. Chen, Zezhun Chen & Dassios, Angelos & Tzougas, George, 2023. "EM estimation for bivariate mixed poisson INAR(1) claim count regression models with correlated random effects," LSE Research Online Documents on Economics 118826, London School of Economics and Political Science, LSE Library.
  102. Shi, Peng & Valdez, Emiliano A., 2011. "A copula approach to test asymmetric information with applications to predictive modeling," Insurance: Mathematics and Economics, Elsevier, vol. 49(2), pages 226-239, September.
  103. Akakpo, Nathalie, 2017. "Multivariate intensity estimation via hyperbolic wavelet selection," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 32-57.
  104. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
  105. Barbiero, A., 2019. "A bivariate count model with discrete Weibull margins," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 91-109.
  106. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
  107. Sasanka Adikari & Norou Diawara, 2024. "Utility in Time Description in Priority Best–Worst Discrete Choice Models: An Empirical Evaluation Using Flynn’s Data," Stats, MDPI, vol. 7(1), pages 1-18, February.
  108. Yanyuan Ma & Marc Genton & Emanuel Parzen, 2011. "Asymptotic properties of sample quantiles of discrete distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 227-243, April.
  109. Cossette, Hélène & Mailhot, Mélina & Marceau, Étienne, 2012. "TVaR-based capital allocation for multivariate compound distributions with positive continuous claim amounts," Insurance: Mathematics and Economics, Elsevier, vol. 50(2), pages 247-256.
  110. Genest, Christian & Segers, Johan, 2010. "On the covariance of the asymptotic empirical copula process," Journal of Multivariate Analysis, Elsevier, vol. 101(8), pages 1837-1845, September.
  111. Oh, Rosy & Jeong, Himchan & Ahn, Jae Youn & Valdez, Emiliano A., 2021. "A multi-year microlevel collective risk model," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 309-328.
  112. Asimit, Alexandru V. & Furman, Edward & Vernic, Raluca, 2010. "On a multivariate Pareto distribution," Insurance: Mathematics and Economics, Elsevier, vol. 46(2), pages 308-316, April.
  113. Yi Qian & Hui Xie, 2015. "Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases," Management Science, INFORMS, vol. 61(3), pages 520-541, March.
  114. Jong-Min Kim & Hyunsu Ju & Yoonsung Jung, 2020. "Copula Approach for Developing a Biomarker Panel for Prediction of Dengue Hemorrhagic Fever," Annals of Data Science, Springer, vol. 7(4), pages 697-712, December.
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