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A simulation study of maximum likelihood estimation in logistic regression wi...
The logistic regression model is widely used to investigate the relationship between a binary outcome Y and a set of potential predictors X. Diop et al. (2011) present... -
New consistent and asymptotically normal parameter estimates for random-graph...
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Model-based clustering and segmentation of time series with changes in regime
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Copula analysis of mixture models
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Deviance Information Criteria for Missing Data Models
The deviance information criterion (DIC) introduced by is directly inspired by linear and generalised linear models, but it is not so naturally defined for missing... -
Mixture of linear mixed models Application to repeated data clustering
The problem of finite mixture analysis from repeated data is considered. Data variability is taken into account through linear mixed models leading to a mixture of... -
Assessing a Mixture Model for Clustering with the Integrated Classification L...
We propose assessing a mixture model in a cluster analysis setting with the inegrated classification likelihood. With this purpose, the observed data are assigned to... -
Model-based clustering for multivariate partial ranking data
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Modeling and numerical study of two phases flow
This thesis describes the modelisation and the simulation of two-phase systems composed of droplets moving in a gas. The two phases interact with each other and the... -
Plugin procedure in segmentation and application to hyperspectral image segme...
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Numerical study of two phase laminar mixed convection nanofluid in elliptic d...
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Mixture models for two-dimensional baseline correction, applied to artifact e...
Baseline correction and artifact removal are important pre-processing steps in analytical chemistry. We propose a correction algorithm using a mixture model in... -
Pattern identification and characterization reveal permutations of organs as ...
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An alternative estimation approach for the heterogeneity linear mixed model
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Bayesian nonparametric Plackett-Luce models for the analysis of preferences f...
International audience -
Information-geometric methods for mixture models
This thesis presents new methods for mixture model learning based on information geometry. We focus on mixtures of exponential families, which encompass a large number... -
A macro-DAG structure based mixture model
In the context of unsupervised classification of multidimensional data, we revisit the classical mixture model in the case where the dependencies among the random... -
Von Mises-Fisher mixture models
In contemporary life directional data are present in most areas, in several forms, aspects and large sizes / dimensions; hence the need for effective methods of...
