lmvar

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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Description file content

Package
lmvar
Type
Package
Title
Linear Regression with Non-Constant Variances
Version
1.3.0
Author
Posthuma Partners
Maintainer
Marco Nijmeijer
Description
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.
License
GPL-3
LazyData
TRUE
Imports
Matrix (>= 1.2-4), matrixcalc (>= 1.0-3), maxLik (>= 1.3-4), stats (>= 3.2.5), parallel (>= 3.4.0), graphics (>= 3.4.0)
RoxygenNote
6.0.1
Suggests
testthat, knitr, rmarkdown, R.rsp, MASS
VignetteBuilder
knitr, R.rsp
ByteCompile
true
NeedsCompilation
no
Packaged
2017-09-07 16:38:03 UTC; Marc
Repository
CRAN
Date/Publication
2017-09-07 16:57:40 UTC

install.packages('lmvar')

1.3.0

a month ago

Marco Nijmeijer

GPL-3

Imports

Matrix (>= 1.2-4), matrixcalc (>= 1.0-3), maxLik (>= 1.3-4), stats (>= 3.2.5), parallel (>= 3.4.0), graphics (>= 3.4.0)

Suggests

testthat, knitr, rmarkdown, R.rsp, MASS

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