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Composite likelihood estimation method for hierarchical Archimedean copulas defined with multivariate compound distributions

  • Published:2019-07 Issue: Volume:172 Page:59-83
  • ISSN:0047-259X
  • Container-title:Journal of Multivariate Analysis
  • language:en
  • Short-container-title:Journal of Multivariate Analysis

Author:

Cossette Hélène,Gadoury Simon-Pierre,Marceau Etienne,Robert Christian Y.

Funder

Natural Sciences and Engineering Research Council of Canada

Chaire en actuariat de l’Université Laval, Canada

Chaire d’Excellence DAMI, France

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Numerical Analysis,Statistics and Probability

Reference33 articles.

1. Hierarchical Kendall copulas: Properties and inference;Brechmann;Canad. J. Statist.,2014

2. Hierarchical Archimedean copulas through multivariate compound distributions;Cossette;Insurance Math. Econom.,2017

3. Efficient algorithms for agglomerative hierarchical clustering methods;Day;J. Classification,1984

4. Spatial composite likelihood inference using local C-vines;Erhardt;J. Multivariate Anal.,2015

5. S.-P. Gadoury, erhcv: Equi-Rank Hierarchical Clustering Validation, R package version 012, 2018.

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1. Estimation;SpringerBriefs in Applied Statistics and Econometrics;2024

2. Composite pseudo-likelihood estimation for pair-tractable copulas such as Archimedean, Archimax and related hierarchical extensions;Journal of Statistical Computation and Simulation;2023-02-21

3. Hypothesis Tests for Structured Rank Correlation Matrices;Journal of the American Statistical Association;2022-07-22

4. On a Rosenblatt-type transformation of multivariate copulas;Econometrics and Statistics;2021-11

5. Outer power transformations of hierarchical Archimedean copulas: Construction, sampling and estimation;Computational Statistics & Data Analysis;2021-03
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