Package: TSsmoothing 0.1.0

TSsmoothing: Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness

It performs the smoothing approach provided by penalized least squares for univariate and bivariate time series, as proposed by Guerrero (2007) and Gerrero et al. (2017). This allows to estimate the time series trend by controlling the amount of resulting (joint) smoothness. --- Guerrero, V.M (2007) <doi:10.1016/j.spl.2007.03.006>. Guerrero, V.M; Islas-Camargo, A. and Ramirez-Ramirez, L.L. (2017) <doi:10.1080/03610926.2015.1133826>.

Authors:L. Leticia Ramirez-Ramirez [aut, cre], Alejandro Islas-Camargo [aut], Victor M. Guerrero [aut]

TSsmoothing_0.1.0.tar.gz
TSsmoothing_0.1.0.zip(r-4.7-any)TSsmoothing_0.1.0.zip(r-4.6-any)TSsmoothing_0.1.0.zip(r-4.5-any)
TSsmoothing_0.1.0.tgz(r-4.6-any)TSsmoothing_0.1.0.tgz(r-4.5-any)
TSsmoothing_0.1.0.tar.gz(r-4.7-any)TSsmoothing_0.1.0.tar.gz(r-4.6-any)
TSsmoothing_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
TSsmoothing/json (API)

# Install 'TSsmoothing' in R:
install.packages('TSsmoothing', repos = c('https://leticiaram.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • emp_agr - Employment in agriculture
  • ltable - Lambda values table.
  • trade - Annual Trade for USA and Mexico

On CRAN:

Conda:

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

1.00 score 259 downloads 10 exports 21 dependencies

Last updated from:0d5315c52d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK158
source / vignettesOK166
linux-release-x86_64OK134
macos-release-arm64OK157
macos-oldrel-arm64OK138
windows-develOK105
windows-releaseOK106
windows-oldrelOK85
wasm-releaseOK92

Exports:corrmvcgraph_trendlambda_valueplot_trendpositive_definitepreliminarpsigma_estimatessigma_zfsmoothing_leveltrend_estimate

Dependencies:clicpp11farverggplot2gluegridExtragtableisobandlabelinglatticelifecycleMASSMatrixR6RColorBrewerrlangS7scalesvctrsviridisLitewithr