V.
Vandewalle, C. Biernacki, G. Celeux & G. Govaert (2013). A
predictive deviance criterion for selecting a generative model in
semi-supervised classification. Computational
Statistics and Data Analysis,
in press.
PS
C.
Biernacki & J. Jacques (2012). A generative model for rank data based on insertion sort
algorithm,
Computational
Statistics and Data Analysis,
in press. PDF
A.
Lourme & C. Biernacki (2013). Simultaneous Gaussian
Model-Based Clustering for Samples of Multiple Origins,
Computational
Statistics,
28(1), 371-391. PDF
A.
Lourme & C. Biernacki (2011). Classification simultanée de
plusieurs échantillons sous contrainte d’égalité des
entropies de partition. Journal
de la Société Française de Statistique,
152(3), 21–33. PDF
A.
Lourme & C. Biernacki (2011). Simultaneous t-Model-Based
Clustering for Data Differing over Time Period: Application for
Understanding Companies Financial Health. Case
Studies in Business, Industry and Government Statistics (CSBIGS),
4(2), 73–82. PDF
C.
Biernacki, G. Celeux & G. Govaert (2010). Exact and Monte
Carlo Calculations of Integrated Likelihoods for the Latent Class
Model. Journal
of Statistical Planning and Inference,
1, 2991-3002. PDF
J.
Jacques & C. Biernacki (2010). Extension of model-based
classification for binary data when training and test populations
differ. Journal
of Applied Statistics,
37(5), 749-766. PDF
C.
Biernacki (2009). Pourquoi les modèles de mélange pour la
classification ? La
Revue de Modulad,
40, 1-22. PDF
I.
Thomas, P. Frankhauser & C. Biernacki (2008). The morphology
of built-up landscapes in Wallonia (Belgium): a classification
using fractal indices. Landscape
and Urban Planning,
84, 99-115. PDF
C.
Biernacki (2007). Degeneracy in the Maximum Likelihood Estimation
of Univariate Gaussian Mixtures for Grouped Data and Behaviour of
the EM Algorithm. Journal
of Scandinavian Statistics,
34, 569-586. PS
J.
Jacques & C. Biernacki (2007). Analyse discriminante sur
données binaires lorsque les populations d’apprentissage et de
test sont différentes. Revue
des Nouvelles Technologies de l'Information, Data Mining et
apprentissage statistique : application en assurance, banque et
marketing,
A1, 109-125. PDF
F.
Beninel & C. Biernacki (2007). Modèles d’extension de la
régression logistique. Revue
des Nouvelles Technologies de l'Information, Data Mining et
apprentissage statistique : application en assurance, banque et
marketing,
A1, 207-218. PDF
C.
Biernacki, G. Celeux, A. Anwuli, G. Govaert & F. Langrognet
(2006).Le logiciel MIXMOD d'analyse de mélange pour la
classification et l'analyse discriminante. La
Revue de Modulad,
35, 25-44. PDF
C.
Biernacki, G. Celeux, G. Govaert & F. Langrognet (2006).
Model-Based Cluster and Discriminant Analysis with the MIXMOD
Software. Computational
Statistics and Data Analysis,
51(2), 587-600. PS
C.
Biernacki (2005). Testing for a Global Maximum of the Likelihood
. Journal
of Computational and Graphical Statistics,
14(3), 657-674. (PDF:
paper
,
appendix)
C.
Biernacki (2004). Initializing EM Using the Properties of its
Trajectories in Gaussian Mixtures. Statistics
and Computing,
14(3), 267-279. PS
C.
Biernacki & S. Chrétien (2003). Degeneracy in the Maximum
Likelihood Estimation of Univariate Gaussian Mixtures with EM.
Statistics
& Probability Letters,
61, 373-382. PS
C.
Biernacki, G. Celeux & G. Govaert (2003). Choosing Starting
Values for the EM Algorithm for Getting the Highest Likelihood in
Multivariate Gaussian Mixture Models. Computational
Statistics and Data Analysis,
41, 561-575. PS
C.
Biernacki, F. Beninel & V. Bretagnolle (2002). A Generalized
Discriminant Rule when Training Population and Test Population
Differ on their Descriptive Parameters. Biometrics,
58(2), 387-397. PS
C.
Biernacki, G. Celeux & G. Govaert (2000). Assessing a Mixture
Model for Clustering with the IntegratedCompleted Likelihood.
IEEE
Transactions on Pattern Analysis and Machine Intelligence,
22(7), 719-725. PS
C.
Biernacki, G. Celeux & G. Govaert (1999). An Improvement of
the NEC Criterion for Assessing the Number of Clusters in a
Mixture Model. Pattern
Recognition Letters,
20(3), 267-272. PS
C.
Biernacki & G. Govaert (1999). Choosing Models in Model-based
Clustering and Discriminant Analysis. Journal
of Statistical Computation and Simulation,
64, 49-71. PS
C.
Biernacki (1999). Précision sur les données et coude de la
vraisemblance pour trouver le nombre de classes dans un mélange.
Revue
de Statistique Appliquée,
47(1), 47-62. PS
