lmvar (1.2.1)

Linear Regression with Non-Constant Variances.


Runs a linear regression 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.

Maintainer: Marco Nijmeijer
Author(s): Posthuma Partners <info@posthuma-partners.nl>

License: GPL-3

Uses: Matrix, matrixcalc, maxLik, R.rsp, MASS, testthat, knitr, rmarkdown

Released over 2 years ago.