Christophe Biernacki
Christophe Biernacki
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Assessing a mixture model for clustering with the integrated completed likelihood
C Biernacki, G Celeux, G Govaert
IEEE transactions on pattern analysis and machine intelligence 22 (7), 719-725, 2000
Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
C Biernacki, G Celeux, G Govaert
Computational Statistics & Data Analysis 41 (3-4), 561-575, 2003
The morphology of built-up landscapes in Wallonia (Belgium): A classification using fractal indices
I Thomas, P Frankhauser, C Biernacki
Landscape and urban planning 84 (2), 99-115, 2008
Model-based cluster and discriminant analysis with the MIXMOD software
C Biernacki, G Celeux, G Govaert, F Langrognet
Computational Statistics & Data Analysis 51 (2), 587-600, 2006
An improvement of the NEC criterion for assessing the number of clusters in a mixture model
C Biernacki, G Celeux, G Govaert
Pattern Recognition Letters 20 (3), 267-272, 1999
Using the classification likelihood to choose the number of clusters
C Biernacki, G Govaert
Computing Science and Statistics, 451-457, 1997
Choosing models in model-based clustering and discriminant analysis
C Biernacki, G Govaert
Journal of Statistical Computation and Simulation 64 (1), 49-71, 1999
Rmixmod: The R package of the model-based unsupervised, supervised, and semi-supervised classification Mixmod library
R Lebret, S Iovleff, F Langrognet, C Biernacki, G Celeux, G Govaert
Journal of Statistical Software 67, 1-29, 2015
Mixture of Gaussians for distance estimation with missing data
E Eirola, A Lendasse, V Vandewalle, C Biernacki
Neurocomputing 131, 32-42, 2014
A generative model for rank data based on insertion sort algorithm
C Biernacki, J Jacques
Computational Statistics & Data Analysis 58, 162-176, 2013
Exact and Monte Carlo calculations of integrated likelihoods for the latent class model
C Biernacki, G Celeux, G Govaert
Journal of Statistical Planning and Inference 140 (11), 2991-3002, 2010
Model-based clustering of Gaussian copulas for mixed data
M Marbac, C Biernacki, V Vandewalle
Communications in Statistics-Theory and Methods 46 (23), 11635-11656, 2017
Model-based co-clustering for ordinal data
J Jacques, C Biernacki
Computational Statistics & Data Analysis 123, 101-115, 2018
L'épreuve des inégalités
H Lagrange
PUF, 2015
Degeneracy in the maximum likelihood estimation of univariate Gaussian mixtures with EM
C Biernacki, S Chrétien
Statistics & probability letters 61 (4), 373-382, 2003
Model-based clustering for multivariate partial ranking data
J Jacques, C Biernacki
Journal of Statistical Planning and Inference 149, 201-217, 2014
A multifractal mass transference principle for Gibbs measures with applications to dynamical Diophantine approximation
AH Fan, J Schmeling, S Troubetzkoy
Proceedings of the London Mathematical Society 107 (5), 1173-1219, 2013
A generalized discriminant rule when training population and test population differ on their descriptive parameters
C Biernacki, F Beninel, V Bretagnolle
Biometrics 58 (2), 387-397, 2002
Model-based clustering of multivariate ordinal data relying on a stochastic binary search algorithm
C Biernacki, J Jacques
Statistics and Computing 26, 929-943, 2016
Initializing EM using the properties of its trajectories in Gaussian mixtures
C Biernacki
Statistics and Computing 14, 267-279, 2004
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