4 citations · 5 across the 2 of their papers we have counts for
5 papers
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…