17 citations · 51 across the 11 of their papers we have counts for
Showing 2016Show all
3 papers · 1 filter
stat.ME2016
Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood
Piotr Sobczyk, Malgorzata Bogdan, Julie Josse
We discuss the problem of estimating the number of principal components in Principal Com- ponents Analysis (PCA). Despite of the importance of the problem and the multitude of solu…
stat.ME2016
Multiple Correspondence Analysis & the Multilogit Bilinear Model
William Fithian, Julie Josse
Multiple Correspondence Analysis (MCA) is a dimension reduction method which plays a large role in the analysis of tables with categorical nominal variables such as survey data. Th…
stat.ME2016
Multinomial Multiple Correspondence Analysis
Patrick J. F. Groenen, Julie Josse
Relations between categorical variables can be analyzed conveniently by multiple correspondence analysis (MCA). %It is well suited to discover relations that may exist between cate…