M4_benchmarks: M4_benchmarks

In jdestefani/MM4Benchmark: Multivariate (multi-univariate) M4 Benchmarks

Description

Function producing the univariate forecasts employing all the benchmark methods of the M4 competition. Adapted from https://github.com/M4Competition/M4-methods/blob/master/Benchmarks%20and%20Evaluation.R

Usage

M4_benchmarks(input, fh)

Arguments

input	Input time series (numeric vector)
fh	Forecasting horizon (numeric scalar)

Value

List containing:

• Naive: h-step forecast for the naive method (numeric vector - length h)

• NaiveSeasonal: h-step forecast for the seasonal naive method (numeric vector - length h)

• SimpleES: h-step forecast for the simple exponential smoothing method (numeric vector - length h)

• HoltWinters: h-step forecast for the Holt-Winters method (numeric vector - length h)

• HoltWintersDamped: h-step forecast for Holt-Winters damped method (numeric vector - length h)

• Theta: h-step forecast for the theta method (numeric vector - length h)

• Combined: h-step forecast for the combined method (numeric vector - length h)

• TimeNaive: Computational time for the naive method (numeric scalar)

• TimeNaiveSeasonal: Computational time for the seasonal naive method (numeric scalar)

• TimeSimpleES: Computational time for the simple exponential smoothing method (numeric scalar)

• TimeHoltWinters: Computational time for the Holt-Winters method (numeric scalar)

• TimeHoltWintersDamped: Computational time for Holt-Winters damped method (numeric scalar)

• TimeTheta: Computational time for the theta method (numeric scalar)

• TimeCombined: Computational time for the combined method (numeric scalar)

Examples

x <- AirPassengers
splitting_point <- round(2*length(x)/3)
x_train <- x[1:splitting_point]
h <- 5
univariate_results <- M4_benchmarks(x_train,h)

jdestefani/MM4Benchmark documentation built on Dec. 20, 2021, 10:05 p.m.