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
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TSF.pdf |TSF.html✨
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.

2.20 score 32 scripts 105 downloads 5 mentions 3 exports 45 dependencies

Last updated 8 years agofrom:9f4807ea94. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 12 2025
R-4.5-winOKMar 12 2025
R-4.5-macOKMar 12 2025
R-4.5-linuxOKMar 12 2025
R-4.4-winOKMar 12 2025
R-4.4-macOKMar 12 2025
R-4.4-linuxOKMar 12 2025
R-4.3-winOKMar 12 2025
R-4.3-macOKMar 12 2025

Exports:fdseriesforecastTSFStructuralBrekwithLongmemory

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo