Package: slm 1.2.0

slm: Stationary Linear Models

Provides statistical procedures for linear regression in the general context where the errors are assumed to be correlated. Different ways to estimate the asymptotic covariance matrix of the least squares estimators are available. Starting from this estimation of the covariance matrix, the confidence intervals and the usual tests on the parameters are modified. The functions of this package are very similar to those of 'lm': it contains methods such as summary(), plot(), confint() and predict(). The 'slm' package is described in the paper by E. Caron, J. Dedecker and B. Michel (2019), "Linear regression with stationary errors: the R package slm", arXiv preprint <arxiv:1906.06583>.

Authors:Emmanuel Caron, Jérôme Dedecker, Bertrand Michel

slm_1.2.0.tar.gz
slm_1.2.0.zip(r-4.7-any)slm_1.2.0.zip(r-4.6-any)slm_1.2.0.zip(r-4.5-any)
slm_1.2.0.tgz(r-4.6-any)slm_1.2.0.tgz(r-4.5-any)
slm_1.2.0.tar.gz(r-4.7-any)slm_1.2.0.tar.gz(r-4.6-any)
slm_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
slm/json (API)

# Install 'slm' in R:
install.packages('slm', repos = c('https://e-caron.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • shan - PM2.5 Data of Shanghai

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 20 scripts 280 downloads 14 exports 8 dependencies

Last updated from:7aafbca19d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK92
source / vignettesOK175
linux-releaseOK96
macos-releaseOK172
macos-oldrelOK124
windows-develOK61
windows-releaseOK54
windows-oldrelOK85
wasm-releaseOK72

Exports:cov_ARcov_efromovichcov_kernelcov_matrix_estimatorcov_methodcov_selectcov_spectralprojgenerative_modelgenerative_processRbootrectangleslmtrapezetriangle

Dependencies:capusheexpmlatticeltsaMASSMatrixsandwichzoo