Package: aplms 0.1.0

aplms: Additive Partial Linear Models with Symmetric Autoregressive Errors

Set of tools for fitting the additive partial linear models with symmetric autoregressive errors of order p, or APLMS-AR(p). This setup enables the modeling of a time series response variable using linear and nonlinear structures of a set of explanatory variables, with nonparametric components approximated by natural cubic splines or P-splines. It also accounts for autoregressive error terms with distributions that have lighter or heavier tails than the normal distribution. The package includes various error distributions, such as normal, generalized normal, Student's t, generalized Student's t, power-exponential, and Cauchy distributions. Chou-Chen, S.W., Oliveira, R.A., Raicher, I., Gilberto A. Paula (2024) <doi:10.1007/s00362-024-01590-w>.

Authors:Shu Wei Chou-Chen [aut, cre, cph], Rodrigo A. Oliveira [aut], Gilberto A. Paula [aut], Sebastian Sanchez Sandi [ctb]

aplms_0.1.0.tar.gz
aplms_0.1.0.zip(r-4.7-any)aplms_0.1.0.zip(r-4.6-any)aplms_0.1.0.zip(r-4.5-any)
aplms_0.1.0.tgz(r-4.6-any)aplms_0.1.0.tgz(r-4.5-any)
aplms_0.1.0.tar.gz(r-4.7-any)aplms_0.1.0.tar.gz(r-4.6-any)
aplms_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
aplms/json (API)

# Install 'aplms' in R:
install.packages('aplms', repos = c('https://swchouchen.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/shuwei325/aplms/issues

Datasets:

On CRAN:

Conda:

3.63 score 43 scripts 344 downloads 13 exports 14 dependencies

Last updated from:1b2e254a1e. Checks:2 NOTE, 7 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE172
source / vignettesOK386
linux-releaseOK277
macos-releaseOK207
macos-oldrelOK235
windows-develNOTE156
windows-releaseOK421
windows-oldrelOK150
wasm-releaseOK306

Exports:aplmsaplms.diag.plotCauchyCnormalGlogisGNormalGstudentinfluenceplot.aplmsLogisILogisIINormalPowerexpStudent

Dependencies:data.tableGPArotationjsonlitelatticeMASSMatrixmgcvmnormtnlmepsychrlistrmutilXMLyaml