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TSF  

Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break
View on CRAN: Click here


Download and install TSF package within the R console
Install from CRAN:
install.packages("TSF")

Install from Github:
library("remotes")
install_github("cran/TSF")

Install by package version:
library("remotes")
install_version("TSF", "0.1.1")



Attach the package and use:
library("TSF")
Maintained by
Dr. Ranjit Kumar Paul
[Scholar Profile | Author Map]
First Published: 2017-07-15
Latest Update: 2017-07-15
Description:
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>.
How to cite:
Dr. Ranjit Kumar Paul (2017). TSF: Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break. R package version 0.1.1, https://cran.r-project.org/web/packages/TSF. Accessed 01 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited TSF R package
View TSF citation profile
Other R packages that TSF depends, imports, suggests or enhances
Complete documentation for TSF
Functions, R codes and Examples using the TSF R package
Some associated functions: StructuralBrek . diffseries . forecastTSF . 
Some associated R codes: TSF.R .  Full TSF package functions and examples
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