40 citations · 81 across the 10 of their papers we have counts for
10 papers
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…
plsRglm: Partial least squares linear and generalized linear regression for processing incomplete datasets by cross-validation and bootstrap techniques with R
F. Bertrand, M. Maumy-Bertrand
The aim of the plsRglm package is to deal with complete and incomplete datasets through several new techniques or, at least, some which were not yet implemented in R. Indeed, not o…
A Sheet of Maple to Compute Second-Order Edgeworth Expansions and Related Quantities of any Function of the Mean of an iid Sample of an Absolutely Continuous Distribution
F. Bertrand, M. Maumy-Bertrand
We designed a completely automated Maple () worksheet for deriving Edgeworth and Cornish-Fisher expansions as well as the acceleration constant of the bootstrap bias-…
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…
AcSel: selecting variables with accuracy in correlated datasets
Jung Nicolas, Frédéric Bertrand, Myriam Maumy-Bertrand
With the emergence of high-throughput technologies, it is possible to measure large amounts of data relatively at low cost. Such situations arise in many fields from sciences to hu…
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…