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.


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install.packages("lmvar")

1.3.0 by Marco Nijmeijer, 2 months ago


Browse source code at https://github.com/cran/lmvar


Authors: Posthuma Partners <info@posthuma-partners.nl>


Documentation:   PDF Manual  


GPL-3 license


Imports Matrix, matrixcalc, maxLik, stats, parallel, graphics

Suggests testthat, knitr, rmarkdown, R.rsp, MASS


See at CRAN