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ForecastTB  

Test Bench for the Comparison of Forecast Methods
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ForecastTB", "1.0.1")



Attach the package and use:
library("ForecastTB")
Maintained by
Neeraj Dhanraj Bokde
[Scholar Profile | Author Map]
First Published: 2020-03-14
Latest Update: 2020-03-14
Description:
Provides a test bench for the comparison of forecasting methods in uni-variate time series. Forecasting methods are compared using different error metrics. Proposed forecasting methods and alternative error metrics can be used. Detailed discussion is provided in the vignette.
How to cite:
Neeraj Dhanraj Bokde (2020). ForecastTB: Test Bench for the Comparison of Forecast Methods. R package version 1.0.1, https://cran.r-project.org/web/packages/ForecastTB. Accessed 31 Mar. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited ForecastTB R package
View ForecastTB citation profile
Other R packages that ForecastTB depends, imports, suggests or enhances
Complete documentation for ForecastTB
Functions, R codes and Examples using the ForecastTB R package
Some associated functions: append_ . choose_ . monte_carlo . plot.prediction_errors . plot_circle . prediction_errors . 
Some associated R codes: Monte_Carlo.R . aastrategy2.R . append_.R . choose_.R . globalVariables.R . plotMethods.R . plot_circle.R . prediction_errors.R .  Full ForecastTB package functions and examples
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