calculateMPEs: Mean Percentage errors for the given data from dataset (MPEs)
In svcuonghvktqs/FORA: A package for time sereis forecast accuracy evaluation

Description Usage Arguments Value Author(s) References See Also Examples

This function calculates and returns list of two dataframes, where the first data frame contains MPEs for the given data, diferent horizons and methods, the second one contains ranked list of the methods according to MPEs. Also the function plots MPEs for different hirizons and methods.

1	calculateMPEs(frame, sort = FALSE)

`frame`	A data frame containing columns "actual", "forecast", "method", and "horizon".
`sort`	logical. If TRUE the resulting list of MPEs dataframe and ranked dataframe of MPEs sorting by average value.

calculateMPEs function calculates and returns list of two dataframes, where the first data frame contains MPEs for the given data, diferent horizons and methods, the second one contains ranked dataframe of the methods according to MPEs. Also the function plots MPEs for different hirizons and methods.

Sai Van Cuong, Maixm Shcherbakov and Andrey Davydenko

Rob J. Hyndman, Anne B. Koehler (2006) Volume title: "International Journal of Forecasting". Chapter title: Another look at measures of forecast accuracy. Chapter pages : (p.679-688). http://eva.fcea.edu.uy/pluginfile.php/109034/mod_resource/content/0/2006_Hyndman_Predicc.pdf.

calculateAvgRelMAEs, calculateGMAPEs, calculateGMRAEs, calculateMAD_MEAN_ratio, calculateMAEs, calculateMAPEs, calculateMASEs, calculateMdAPEs, calculateMSEs, calculatePB_MAEs, calculateRMSEs, calculateSMAPEs, calculateSMdAPEs.

calculateMPEs(frame = FORAYearForecast)
calculateMPEs(frame = FORAYearForecast, sort = TRUE)
data1 <- subset(FORAYearForecast, actual >= 5000| forecast < 8000)
data2 <- FORAYearForecast[1:300,]
calculateMPEs(frame = data1, sort = TRUE)
calculateMPEs(frame = data2, sort = TRUE)