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 MAD_MEAN_ratio for the given data, diferent horizons and methods, the second one contains ranked list of the methods according to MAD_MEAN_ratio. Also the function plots MAD_MEAN_ratio for different hirizons and methods.

1	calculateMAD_MEAN_ratio(frame, sort = FALSE)

`frame`	A data frame containing columns "actual", "forecast", "method" and "horizon".
`sort`	logical. If TRUE the resulting list of MAD_MEAN_ratio dataframe and ranked dataframe of MAD_MEAN_ratio sorting by average value. If not specify by default.

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

Sai Van Cuong, Maixm Shcherbakov and Andrey Davydenko

Stephan Kolassa and Wolfgang Schütz: "The International Journal of Applied Forecasting". Title: Advantages of the MAD/Mean Ratio over the MAPE. (p.40-43). https://econpapers.repec.org/article/forijafaa/y_3a2007_3ai_3a6_3ap_3a40-43.htm.

S. D. Prestwich, R. Rossi, S. A. Tarim and B. Hnich: "Mean-Based Error Measures for Intermittent Demand Forecasting". https://arxiv.org/pdf/1310.5663.pdf.

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

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