Explorative multivariate statistics in Python
A Python 3 implementation of orthogonal projection to latent structures
Implementation of a Partial Least Squares Regressor
R package for High dimensional data analysis and integration with O2PLS!
Algorithmic framework for measuring feature importance, outlier detection, model applicability evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.
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.
Archived repo (see Readme) - R package for regression and discrimination, with special focus on chemometrics and high-dimensional data.
Archived repo - This R Package is not developed anymore (only maintenance). It was replaced by R package rchemo
R package plsdepot
Fast CPU and GPU Python implementations of Improved Kernel PLS by Dayal and MacGregor (1997) and Shortcutting Cross-Validation by Engstrøm (2024).
📈 Ordered Homogeneity Pursuit Lasso for Group Variable Selection
The HotellingEllipse package helps draw the Hotelling's T-squared ellipse on a PCA or PLS score scatterplot by computing the Hotelling's T-squared statistic and providing the ellipse's coordinates, semi-minor, and semi-major axes lengths.
Specialized linear, polynomial (including equality constraints on points and slopes), multivariate and nonlinear regression/curve fitting functions.
R scripts for predicting soil organic carbon using soil spectral library from visible, near-infrared and shortwave-infrared (VNIR) and middle-infrared (MIR) using LASSO and PLS regression methods and the target-oriented cross-validation strategy.
Correlation for African Soil between chemistry and fertility data using Logistic Regression. Treatment of infrared (FTIR) spectra by machine learning.
Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."
Computation of training set (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm (2024).
PLS Lesson
Prediction of Miles per gallon (MPG) Using Cars Dataset
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