Want to understand how multivariate linear regression really works under the hood? In this video, we build it from scratch in C++—no machine learning libraries, just raw code and linear algebra. Ideal ...

This paper considers the problem of jointly decomposing a set of time series variables into cyclical and trend components, subject to sets of stochastic linear restrictions among these cyclical and ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

A simple heuristic is proposed for constructing robust experimental designs for multivariate generalized linear models. The method is based on clustering a set of local optimal designs. A method for ...

This is a preview. Log in through your library . Abstract After a hypothesis about some linear multivariate statistical model has been tested and rejected (e. g., in a MANOVA), many researchers employ ...