lmvar (1.5.2)

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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.

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

License: GPL-3

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

Released 6 months ago.

8 previous versions



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