Pinned Repositories
507-Project
601-Project
601 Project
700-Project
aMTM
Adaptive Multiple-Try Metropolis algorithm
aMTM-simulations
Simulation code for the aMTM article (Fontaine and Bédard, 2020+)
BCI-Experiments
BFFM-BCI
Bayesian Functional Factor Model for EEG-Based Brain-Computer Interfaces
fontaine618.github.io
KLR
Kernel Logistic Regression
MTSGL
Mutli-task regression with sparse group regularization using a proximal ADMM
fontaine618's Repositories
fontaine618/KLR
Kernel Logistic Regression
fontaine618/507-Project
fontaine618/fontaine618.github.io
fontaine618/MTSGL
Mutli-task regression with sparse group regularization using a proximal ADMM
fontaine618/601-Project
601 Project
fontaine618/700-Project
fontaine618/aMTM
Adaptive Multiple-Try Metropolis algorithm
fontaine618/aMTM-simulations
Simulation code for the aMTM article (Fontaine and Bédard, 2020+)
fontaine618/BCI-Experiments
fontaine618/BFFM-BCI
Bayesian Functional Factor Model for EEG-Based Brain-Computer Interfaces
fontaine618/CNTools
This is a read-only mirror of the Bioconductor SVN repository. Package Homepage: http://bioconductor.org/packages/devel/bioc/html/CNTools.html Bug Reports: https://support.bioconductor.org/p/new/post/?tag_val=CNTools.
fontaine618/crime
fontaine618/fastR
Examples of speeding up R with C++ and FORTRAN
fontaine618/git-example
fontaine618/LSVCMM
Locally Sparse Varying Coefficients Mixed Model
fontaine618/LSVCMM-Experiments
Experiments accompnying the LSVCMM paper
fontaine618/MCox
Multi-task sparse Cox model
fontaine618/Microbiome-Differential-Ratio-Analysis
fontaine618/MSTweedie
Multi-source sparse Tweedie modelling
fontaine618/MTcox
Multi-task sparse Cox model
fontaine618/NAIVI
Network Node Variable Imputation
fontaine618/prep_workshop_2021
UM Stats Prep Workshop 2021
fontaine618/qr2020
fontaine618/sithon
fontaine618/TCGA2STAT
:exclamation: This is a read-only mirror of the CRAN R package repository. TCGA2STAT — Simple TCGA Data Access for Integrated Statistical Analysis in R. Homepage: http://www.liuzlab.org/TCGA2STAT/
fontaine618/The-Elements-of-Statistical-Learning-Python-Notebooks
A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book
fontaine618/UMSBCC-Experiment-Management
Experiment Management with batchtools (R) and pypet (Python)
fontaine618/VCM-Experiments
Experiments accompanying the LSVCMM
fontaine618/VCMM
fontaine618/website-content
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