References - Alexandre Lourme

Université de Bordeaux - Collège DSPEG - Master 2 Finance Quantitative & Actuariat - Automne 2016
Scoring Appliqué à la Détection du Risque
References
[1] Hirotogu Akaike. Information theory and an extension of the maximum likelihood principle. In Selected Papers
of Hirotugu Akaike, pages 199–213. Springer, 1998.
[2] Jeffrey L Andrews and Paul D Mcnicholas. Model-based clustering, classification, and discriminant analysis via
mixtures of multivariate t-distributions. Statistics and Computing, 22(5):1021–1029, 2012.
[3] Jeffrey L Andrews, Paul D McNicholas, and Maintainer Jeffrey L Andrews. Package ‘teigen’. 2015.
[4] Mireille Bardos. Analyse discriminante: application au risque et scoring financier. Dunod, 2001.
[5] Laurent Bergé, Charles Bouveyron, and Stéphane Girard. HDclassif: An R package for model-based clustering
and discriminant analysis of high-dimensional data. Journal of Statistical Software, 46(6):1–29, 2012.
[6] Przemysław Biecek, Ewa Szczurek, Martin Vingron, and Jerzy Tiuryn. The R package bgmm: Mixture modeling
with uncertain knowledge. Journal of Statistical Software, 47(3):1–32, 2012.
[7] Christophe Biernacki, Thibault Deregnaucourt, and Vincent Kubicki. Model-based clustering with mixed/missing
data using the new software mixtcomp. In CMStatistics 2015 (ERCIM 2015), 2015.
[8] Charles BOUVEYRON. Hdclassif: an r package for model-based classification of high-dimensional data. Talk,
Université Paris, 1, 2012.
[9] Anderson Rodrigo da Silva. biotools, Tools for Biometry and Applied Statistics in Agricultural Science, 2015.
[10] MODAL Team INRIA Lille Nord Europe. MixtComp MOdels for Data Analysis and Learning. https://
modal.lille.inria.fr/wikimodal/doku.php?id=mixtcomp, 2015.
[11] Chris Fraley and Adrian E. Raftery. Model-based clustering, discriminant analysis and density estimation. Journal
of the American Statistical Association, 97:611–631, 2002.
[12] Chris Fraley, Adrian E. Raftery, Thomas Brendan Murphy, and Luca Scrucca. mclust Version 4 for R: Normal
Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation, 2012.
[13] Alan Genz, Frank Bretz, Tetsuhisa Miwa, Xuefei Mi, Friedrich Leisch, Fabian Scheipl, and Torsten Hothorn.
mvtnorm: Multivariate normal and t distributions. R package version 0.9-2, URL http://CRAN. R-project.
org/package= mvtnorm, 2008.
[14] Gérard Govaert. Data analysis. John Wiley & Sons, 2013.
[15] Selcuk Korkmaz, Dincer Goksuluk, and Gokmen Zararsiz. Mvn: An r package for assessing multivariate normality.
The R Journal, 6(2):151–162, 2014.
[16] Rémi Lebret, Serge Iovleff, Florent Langrognet, Christophe Biernacki, Gilles Celeux, and Gérard Govaert. Rmixmod: the r package of the model-based unsupervised, supervised and semi-supervised classification mixmod
library. Journal of Statistical Software, pages In–press, 2015.
[17] Remi Lebret, Serge Iovleff, Florent Langrognet, Maintainer Remi Lebret, and LinkingTo Rcpp. Package ‘rmixmod’. 2012.
[18] PD McNicholas, KR Jampani, AF McDaid, TB Murphy, and L Banks. pgmm: Parsimonious gaussian mixture
models. R package version, 1:24–47, 2011.
[19] Gilbert Saporta. Probabilités, analyse des données et statistique. Editions Technip, 2011.
[20] Gideon Schwarz et al. Estimating the dimension of a model. The annals of statistics, 6(2):461–464, 1978.
A. Lourme, Faculté d’économie, gestion & AES, Université de Bordeaux http://alexandrelourme.free.fr
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