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Hassani.Silva  

A Test for Comparing the Predictive Accuracy of Two Sets of Forecasts
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Install from CRAN:
install.packages("Hassani.Silva")

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library("remotes")
install_github("cran/Hassani.Silva")

Install by package version:
library("remotes")
install_version("Hassani.Silva", "1.0")



Attach the package and use:
library("Hassani.Silva")
Maintained by
Leila Marvian Mashhad
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-13
Latest Update: 2023-01-13
Description:
A non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS Predictive Accuracy (KSPA) test. The KSPA test is able to serve two distinct purposes. Initially, the test seeks to determine whether there exists a statistically significant difference between the distribution of forecast errors, and secondly it exploits the principles of stochastic dominance to determine whether the forecasts with the lower error also reports a stochastically smaller error than forecasts from a competing model, and thereby enables distinguishing between the predictive accuracy of forecasts. KSPA test has been described in : Hassani and Silva (2015) .
How to cite:
Leila Marvian Mashhad (2023). Hassani.Silva: A Test for Comparing the Predictive Accuracy of Two Sets of Forecasts. R package version 1.0, https://cran.r-project.org/web/packages/Hassani.Silva
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Functions, R codes and Examples using the Hassani.Silva R package
Some associated functions: KSPA . 
Some associated R codes: KSPA.R .  Full Hassani.Silva package functions and examples
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