calculateRMSEs: Root Mean square errors for the given data from...
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 RMSEs for the given data, diferent horizons and methods, the second one contains ranked list of the methods according to RMSEs. Also the function plots RMSEs for different hirizons and methods.

1	calculateRMSEs(frame, sort = FALSE)

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

calculateRMSEs function calculates and returns list of two dataframes, where the first data frame contains RMSEs for the given data, diferent horizons and methods, the second one contains ranked dataframe of the methods according to RMSEs. Also the function plots RMSEs 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, calculateMPEs, calculateMSEs, calculatePB_MAEs, calculateSMAPEs, calculateSMdAPEs.

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