1.1k citations · 1.2k across the 10 of their papers we have counts for
11 papers
COMBSS: Best Subset Selection via Continuous Optimization
Sarat Moka, Benoit Liquet, Houying Zhu +1
The problem of best subset selection in linear regression is considered with the aim to find a fixed size subset of features that best fits the response. This is particularly chall…
Nonstationary Spatial Process Models with Spatially Varying Covariance Kernels
Sébastien Coube-Sisqueille, Sudipto Banerjee, Benoît Liquet
Building spatial process models that capture nonstationary behavior while delivering computationally efficient inference is challenging. Nonstationary spatially varying kernels (se…
Understanding links between water-quality variables and nitrate concentration in freshwater streams using high-frequency sensor data
Claire Kermorvant, Benoit Liquet, Guy Litt +5
Real time monitoring using in situ sensors is becoming a common approach for measuring water quality within watersheds. High frequency measurements produce big data sets that prese…
Improving performances of MCMC for Nearest Neighbor Gaussian Process models with full data augmentation
Sébastien Coube-Sisqueille, Benoît Liquet
Even though Nearest Neighbor Gaussian Processes (NNGP) alleviate considerably MCMC implementation of Bayesian space-time models, they do not solve the convergence problems caused b…
Estimation of Semi-Markov Multi-state Models: A Comparison of the Sojourn Times and Transition Intensities Approaches
Azam Asanjarani, Benoit Liquet, Yoni Nazarathy
Semi-Markov models are widely used for survival analysis and reliability analysis. In general, there are two competing parameterizations and each entails its own interpretation and…
Classification Algorithm for High Dimensional Protein Markers in Time-course Data
Souvik Banerjee, Gajendra K. Vishwakarma, Atanu Bhattacharjee
Identification of biomarkers is an emerging area in Oncology. In this article, we develop an efficient statistical procedure for classification of protein markers according to thei…
A Unified Parallel Algorithm for Regularized Group PLS Scalable to Big Data
Pierre Lafaye de Micheaux, Benoit Liquet, Matthew Sutton
Partial Least Squares (PLS) methods have been heavily exploited to analyse the association between two blocs of data. These powerful approaches can be applied to data sets where th…
CEoptim: Cross-Entropy R Package for Optimization
Tim Benham, Qibin Duan, Dirk P. Kroese +1
The cross-entropy (CE) method is simple and versatile technique for optimization, based on Kullback-Leibler (or cross-entropy) minimization. The method can be applied to a wide ran…
Estimation of extended mixed models using latent classes and latent processes: the R package lcmm
Cécile Proust-Lima, Viviane Philipps, Benoit Liquet
The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the estimation of mixed models and latent class mix…
A universal approximate cross-validation criterion and its asymptotic distribution
Daniel Commenges, Cécile Proust-Lima, Cécilia Samieri +1
A general framework is that the estimators of a distribution are obtained by minimizing a function (the estimating function) and they are assessed through another function (the ass…
ClustOfVar: An R Package for the Clustering of Variables
M. Chavent, V. Kuentz, B. Liquet +1
Clustering of variables is as a way to arrange variables into homogeneous clusters, i.e., groups of variables which are strongly related to each other and thus bring the same infor…