lmvar: Linear Regression with Non-Constant Variances

Runs a linear-like regression with in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.

Package details

AuthorPosthuma Partners <[email protected]>
MaintainerMarco Nijmeijer <[email protected]>
Package repositoryView on CRAN
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lmvar documentation built on May 7, 2018, 5:05 p.m.