When Gaussian errors are inappropriate in a multivariate linear regression setting, it is often assumed that the errors are iid from a distribution that is a scale mixture of multivariate normals.

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 ...

A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative ...

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 ...

Regression is a statistical tool used to understand and quantify the relation between two or more variables. Regressions range from simple models to highly complex equations. The two primary uses for ...

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...