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ORCIDJournal of Multivariate Analysis, Volume 119
Volume 119, August 2013
- Oliver Grothe, Stephan Nicklas:
Vine constructions of Lévy copulas. 1-15 - Armin Hatefi
, Mohammad Jafari Jozani:
Fisher information in different types of perfect and imperfect ranked set samples from finite mixture models. 16-31 - Areski Cousin, Elena Di Bernardino:
On multivariate extensions of Value-at-Risk. 32-46 - Xavier Bry, Catherine Trottier, Thomas Verron, Fréderic Mortier:
Supervised component generalized linear regression using a PLS-extension of the Fisher scoring algorithm. 47-60 - Axel Bücher, Stanislav Volgushev:
Empirical and sequential empirical copula processes under serial dependence. 61-70 - Haixiang Zhang, Hui Zhao, Jianguo Sun, Dehui Wang, KyungMann Kim:
Regression analysis of multivariate panel count data with an informative observation process. 71-80 - Elena Di Bernardino, Véronique Maume-Deschamps, Clémentine Prieur:
Estimating a bivariate tail: A copula based approach. 81-100 - Jakob Stöber, Harry Joe, Claudia Czado:
Simplified pair copula constructions - Limitations and extensions. 101-118 - Ralf Hielscher:
Kernel density estimation on the rotation group and its application to crystallographic texture analysis. 119-143 - Haruhiko Ogasawara:
Asymptotic cumulants of ability estimators using fallible item parameters. 144-162 - Daniel E. Osborne, Vic Patrangenaru, Leif Ellingson, David Groisser, Armin Schwartzman:
Nonparametric two-sample tests on homogeneous Riemannian manifolds, Cholesky decompositions and Diffusion Tensor Image analysis. 163-175 - Andreas Artemiou, Bing Li:
Predictive power of principal components for single-index model and sufficient dimension reduction. 176-184 - Tianqing Liu, Xiaohui Yuan, Zhaohai Li, Yuanzhang Li:
Empirical and weighted conditional likelihoods for matched case-control studies with missing covariates. 185-199 - Ashis SenGupta, Sungsu Kim, Barry C. Arnold:
Inverse circular-circular regression. 200-208 - Muni S. Srivastava, Shota Katayama, Yutaka Kano:
Corrigendum to "A two sample test in high dimensional data" [J. Multivariate Analysis 114 (2013) 349-358]. 209
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