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Section: New Results
Resampling and classification
Participant : Alain Celisse.
This is a joint work with Tristan Mary-Huard (INRA).
We extended known results about leave-one-out to the case of leave-p-out for the
Overall Objectives
Research Program
Application Domains
New Software and Platforms
- BlockCluster package for co-clustering
- clere package for high dimensional regression
- Clustericat package for correlated categorical variable
- CoModes package for correlated categorical variables
- CorReg package for correlated variables in regression
- HDPenReg package for penalized regressions in high dimension
- FunFEM package for functional data
- FunHDDC package for functional data
- Galaxy-Modal platform
- metaMA package for meta-analysis of microarray data
- metaRNASeq package for meta-analysis of RNA-Seq data
- MixCluster package for correlated mixed variables
- MIXMOD and Rmixmod package for mixed data
- MixtComp package for full mixed data
- MPAgenomics package for multi-patient analysis of genomic markers
- RankCluster package to cluster ranking data
- rtkpp package: STK++ Integration To R Using Rcpp
- STK++ release 0.8.4: The Statistical ToolKit
New Results
- Highlights of the Year
- Model for conditionally correlated categorical data
- Model for conditionally correlated categorical data
- Mixture model for mixed kind of data
- Mixture of Gaussians with Missing Data
- Clustering and variable selection in regression
- Model-based clustering for multivariate partial ranking data
- Generative models for correlated variables in regression
- Model-based clustering for multivariate partial ordinal data
- Clustering for functional data into discriminative subspaces
- Degeneracy in multivariate Gaussian mixtures
- Auto-Associative Models
- Resampling and density estimation
- Resampling and classification
- Kernel change-point
- Normality test in RKHS
- Differential meta-analysis of RNA-seq data from multiple studies
- Multi-patient analysis of genomic markers
- Scan statistics for dependent data
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography
Overall Objectives
Research Program
Application Domains
New Software and Platforms
- BlockCluster package for co-clustering
- clere package for high dimensional regression
- Clustericat package for correlated categorical variable
- CoModes package for correlated categorical variables
- CorReg package for correlated variables in regression
- HDPenReg package for penalized regressions in high dimension
- FunFEM package for functional data
- FunHDDC package for functional data
- Galaxy-Modal platform
- metaMA package for meta-analysis of microarray data
- metaRNASeq package for meta-analysis of RNA-Seq data
- MixCluster package for correlated mixed variables
- MIXMOD and Rmixmod package for mixed data
- MixtComp package for full mixed data
- MPAgenomics package for multi-patient analysis of genomic markers
- RankCluster package to cluster ranking data
- rtkpp package: STK++ Integration To R Using Rcpp
- STK++ release 0.8.4: The Statistical ToolKit
New Results
- Highlights of the Year
- Model for conditionally correlated categorical data
- Model for conditionally correlated categorical data
- Mixture model for mixed kind of data
- Mixture of Gaussians with Missing Data
- Clustering and variable selection in regression
- Model-based clustering for multivariate partial ranking data
- Generative models for correlated variables in regression
- Model-based clustering for multivariate partial ordinal data
- Clustering for functional data into discriminative subspaces
- Degeneracy in multivariate Gaussian mixtures
- Auto-Associative Models
- Resampling and density estimation
- Resampling and classification
- Kernel change-point
- Normality test in RKHS
- Differential meta-analysis of RNA-seq data from multiple studies
- Multi-patient analysis of genomic markers
- Scan statistics for dependent data
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography