README.md

In svcuonghvktqs/FORA: A package for time sereis forecast accuracy evaluation

FORA: A package for time sereis forecast accuracy evaluation

The package FORA includes a set of functions to load data, to visualize forecast features and for making significant conclusion about difference between results obtained by user-defined forecasting models.The comparison performed according build-in error measures, such as common-used as well as advanced and stable measures.

Install from GitHub:

  install.packages("devtools")
  devtools::install_github("svcuonghvktqs/FORA")

To get help for the package:

  library(FORA)
  help(package = "FORA")

Set of functions:

Function for forecast data visualization:

• plotPRD(): Prediction-Realization Diagram
• plotAPEs(): Boxplot of Absolute Percentage errors
• plotPEs(): Boxplot of Percentage errors

Function time sereis forecast accuracy evaluation

• calculateMAEs(): Mean Absolute errors
• calculateMSEs(): Mean square errors
• calculateRMSEs(): Root Mean square errors
• calculateMAPEs(): Mean Absolute Percentage errors
• calculateMdAPEs(): Median Absolute Percentage errors
• calculateMPEs(): Mean Percentage errors
• calculateGMAPEs(): Geometric Mean Absolute Percentage error
• calculateSMAPEs(): Symmetric Mean Absolute Percentage Errors
• calculateSMdAPEs(): Symmetric Median Absolute Percentage Errors
• calculateGMRAEs(): Geometric Mean Relative Absolute Error
• calculateMASEs(): Mean Absolute Scaled Erro
• calculatePB_MAEs(): Precentage Better(MAE)
• calculateMAD_MAEN_ratio():
• calculateAvgRelMAEs(): Average Relative Mean Absolute Error

Usage

Prediction-Realization Diagram for the given data from dataset:

# plotPRD(df, useLogs = FALSE, xlim = NULL, ylim = NULL)
# examples:
library(forecast)
plotPRD(df = FORAYearForecast)

Boxplot of Absolute Percentage errors:

# boxplotAPEs(df, useLogs = NULL, notch = FALSE, limits = NULL, showOutliers = NULL)
# example:
boxplotAPEs(FORAYearForecast)

Time sereis forecast accuracy evaluation:

# calculateMAEs(frame, sort = FALSE)
calculateMAEs(frame = FORAYearForecast)

calculateAvgRelMAEs(frame = FORAYearForecast, frame2 = FORAYearSeries)

calculateGMRAEs(frame = FORAYearForecast, benchmark_method = "NAIVE2")

svcuonghvktqs/FORA documentation built on May 20, 2019, 9:57 a.m.