2 citations · 2 across the 1 of their papers we have counts for
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Post-clustering difference testing: valid inference and practical considerations
Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut +1
Clustering is part of unsupervised analysis methods that consist in grouping samples into homogeneous and separate subgroups of observations also called clusters. To interpret the…
Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach
Quentin Clairon, Chloé Pasin, Irene Balelli +2
We present a parameter estimation method for nonlinear mixed effect models based on ordinary differential equations (NLME-ODEs). The method presented here aims at regularizing the…
Random forests for high-dimensional longitudinal data
Louis Capitaine, Robin Genuer, Rodolphe Thiébaut
Random forests is a state-of-the-art supervised machine learning method which behaves well in high-dimensional settings although some limitations may happen when , the number of…