lmvar 1.5.2

Linear Regression with Non-Constant Variances

Released May 16, 2019 by Marco Nijmeijer

This package cannot yet be used with Renjin because there was a problem building the package using Renjin's toolchain. View Build Log


maxLik 1.3-6 Matrix 1.2-17 matrixcalc 1.0-3

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.