40 citations · 81 across the 10 of their papers we have counts for
7 papers · 1 filter
Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics
Marie Chion, Christine Carapito, Frédéric Bertrand
Imputing missing values is common practice in label-free quantitative proteomics. Imputation aims at replacing a missing value with a user-defined one. However, the imputation itse…
Determining the Number of Components in PLS Regression on Incomplete Data
Titin Agustin Nengsih, Frédéric Bertrand, Myriam Maumy-Bertrand +1
Partial least squares regression---or PLS---is a multivariate method in which models are estimated using either the SIMPLS or NIPALS algorithm. PLS regression has been extensively…
A random model for multidimensional fitting method
Hiba Alawieh, Frédéric Bertrand, Myriam Maumy-Bertrand +2
Multidimensional fitting (MDF) method is a multivariate data analysis method recently developed and based on the fitting of distances. Two matrices are available: one contains the…
Cross validating extensions of kernel, sparse or regular partial least squares regression models to censored data
Frédéric Bertrand, Philippe Bastien, Myriam Maumy-Bertrand
When cross-validating standard or extended Cox models, the commonly used criterion is the cross-validated partial loglikelihood using a naive or a van Houwelingen scheme -to make e…
selectBoost: a general algorithm to enhance the performance of variable selection methods in correlated datasets
Ismaïl Aouadi, Nicolas Jung, Raphael Carapito +4
Motivation: With the growth of big data, variable selection has become one of the major challenges in statistics. Although many methods have been proposed in the literature their p…
New developments in Sparse PLS regression
Jérémy Magnanensi, Myriam Maumy-Bertrand, Nicolas Meyer +1
Methods based on partial least squares (PLS) regression, which has recently gained much attention in the analysis of high-dimensional genomic datasets, have been developed since th…
A new Universal Resample Stable Bootstrap-based Stopping Criterion in PLS Components Construction
Jérémy Magnanensi, Frédéric Bertrand, Myriam Maumy-Bertrand +1
We develop a new robust stopping criterion in Partial Least Squares Regressions (PLSR) components construction characterised by a high level of stability. This new criterion is def…