Development repository for the Bioconductor package 'mixOmics '
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Updated
Oct 2, 2024 - R
Development repository for the Bioconductor package 'mixOmics '
Markov random fields with covariates
MoMA: Modern Multivariate Analysis in R
manage ordinations and render biplots in a tidyverse workflow
Case Study in ranking U.S. cities based on a single linear combination of rating variables. Dimensionality techniques used in the analysis are Principal Component Analysis (PCA), Factor Analysis (FA), Canonical Correlation Analysis (CCA)
R package for multivariate statistic protocols for integrating archaeometric data (geochemical, mineralogical, petrographic)
Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."
Euclidean Distance Matrix Analysis in R
The MultiHazard R package provides tools for stationary multivariate statistical modeling such as of the joint distribution of MULTIple co-occurring HAZARDs.
This repository contains R code that explains graphically how a few different multivariate statistical techniques work. Topics covered are distance measures, principal component analysis, permutational analysis of variance, and partial least squares regression.
Classification of the federal electoral districts of Mexico according to their level of electoral complexity.
Classification of the states of Mexico according to their level of electoral complexity.
R package for estimation of elliptical extreme quantile regions
A robust deterministic affine-equivariant algorithm for multivariate location and scatter
Analysis of commonly consumed coffee brews by untargeted metabolomics. A collection of R scripts for statistical analysis of data.
Statistical and Computational methods for Microbiome Studies.
My scripts from BL5233 lectures and practicals.
Advanced Multivariate Statistics project
Simulations for an article about extreme quantile region estimation
Predict the activity of smartphone users (walking, sitting, lying) based on high dimensional sensor data.
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