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.

Trimmed L-moments and L-comoments for robust statistics.

Development repository for the Bioconductor package 'mixOmics '

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.

Multivariate data analysis using geometric algorithms made easy!

The purpose of this report is to investigate the historical dataset processed.heartdisease.txt that includes 303 patients at risk of heart disease displaying 14 different recorded fields.

Robust transfer function analysis code for magnetotellurics

The MultiHazard R package provides tools for stationary multivariate statistical modeling such as of the joint distribution of MULTIple co-occurring HAZARDs.

Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！

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

Correspondence Analysis in R and Python

Cal Poly Spring 2024 STAT 419 Applied Multivariate Statistics

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

Synthesize, analyze, and visualize biological oceanography data

电子科技大学 2020 级《多元统计分析》课程代码。

R-based project that utilizes multivariate analysis of Spotify Metrics; specifically multiple multivariate regression and MANOVA.

Markov random fields with covariates

This project was carried out in partial fulfillment of the TUM course Machine Learning for Graphs and Sequential Data (IN2323)