Learn how to use multivariate regression models to compare, control, and test the effects of interventions or treatments on multiple outcomes in data analysis.

2.4. Partial Least Squares Regression PLSR, one of the most popular multivariate modeling methods, performs well for regressing spectra where the number of independent variables (X spectral matrix) is ...

The cox regression analysis was performed to select independent risk factors and develop nomogram. Subsequently, ROC curve, calibration curve and decision curve were drawn to thoroughly evaluate the ...

This repository implements the core function of paper "Sparse Multi-Response Tensor Regression for Alzheimer's Disease Study With Multivariate Clinical Assessments". Firstly, we generate the patterns ...

Describe the bug I want to do regularized multivariate regression with sqrt_lasso. the endogenous variable dy is of shape 128x64 and exogenous variable x is of shape 128x64 also.

In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...

Determining Genetic Causal Variants Through Multivariate Regression Using Mixture Model Penalty V. S. Sundar 1,2 * Chun-Chieh Fan 1,3 Dominic Holland 1,4 Anders M. Dale 1,2,4,5 * ...