Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Development repository for the Bioconductor package 'mixOmics '

Explorative multivariate statistics in Python

应用多元统计分析（高慧璇版）自学材料

Python library to implement advanced trading strategies using machine learning and perform backtesting.

The MetaRbolomics book. A review of R packages in BioC, CRAN, gitlab and github.

(Multiblock) Partial Least Squares Regression for Python

Markov random fields with covariates

MoMA: Modern Multivariate Analysis in R

manage ordinations and render biplots in a tidyverse workflow

Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.

Library that combines control engineering, dynamic simulation and machine learning on time-series. Developed to describe industrial processes and -automation. Lightweight, robust and fast for use in advanced analytics. Built on .NET to run anywhere.

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)

Biomedical Feature Selection for Machine Learning Models

Repository implementing MLJ interface for MultivariateStats models.

mVARbox is a Matlab toolbox for uni/multivariate data series analysis in both time/space and frequency domains, with focus on mutivariate autoregressive (VAR) models

R package for multivariate statistic protocols for integrating archaeometric data (geochemical, mineralogical, petrographic)

Project repository of the Matters Arising commentary "Multivariate BWAS can be replicable with moderate sample sizes in some cases""

Maestria-Computo-Estadistico CIMAT 2018-2019