Package: TSF 0.1.1

TSF: Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break

Forecasting of long memory time series in presence of structural break by using TSF algorithm by Papailias and Dias (2015) <doi:10.1016/j.ijforecast.2015.01.006>.

Authors:Sandipan Samanta, Ranjit Kumar Paul and Dipankar Mitra

TSF_0.1.1.tar.gz
TSF_0.1.1.zip(r-4.7-any)TSF_0.1.1.zip(r-4.6-any)TSF_0.1.1.zip(r-4.5-any)
TSF_0.1.1.tgz(r-4.6-any)TSF_0.1.1.tgz(r-4.5-any)
TSF_0.1.1.tar.gz(r-4.7-any)TSF_0.1.1.tar.gz(r-4.6-any)
TSF_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
TSF/json (API)

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

On CRAN:

Conda:

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

2.28 score 38 scripts 227 downloads 5 mentions 3 exports 31 dependencies

Last updated from:9f4807ea94. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK136
source / vignettesOK209
linux-releaseOK141
macos-releaseOK139
macos-oldrelOK116
windows-develOK89
windows-releaseOK81
windows-oldrelOK81
wasm-releaseOK105

Exports:fdseriesforecastTSFStructuralBrekwithLongmemory

Dependencies:clicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelmtestmagrittrnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo