QualityMeasuresForecasting: Quality Measures for Forecasting

In Mthrun/TSAT: Time Series Analysis Tools (TSAT)

Quality Measures for Forecasting

Description

Conventional Quality Measures for Forecasting

Usage

QualityMeasuresForecasting(Y,FOR,Indices,Mase_Season=1,NonDuplicatedForecasts=FALSE,Silent=TRUE)

Arguments

Y	1:n vector of ordered and regular time series values
FOR	1:n vector of ordered and regular forecast values in the same odering as Y
Indices	default all values, sometimes its usefull to restrict the evaluation
Mase_Season	Seasonlaity for MASE, i.e. stepsize, Default(1) means against naiv model
Silent	TRUE: No Warnings or errors are given back

Details

bias computes the average amount by which actual is greater than predicted.

rae divides sum(ae(actual, predicted)) by sum(ae(actual, mean(actual))), meaning that it provides the absolute error of the predictions relative to a naive model that predicted the mean for every data point.

rse divides sse(actual, predicted) by sse(actual, mean(actual)), meaning that it provides the squared error of the predictions relative to a naive model that predicted the mean for every data point.

MRD = MRD(x,y) - Mean of the root errors. (Sum of the root errors / length(x)) with length = sqrt(a^2 + b^2) - Length of the complex number with real part the errors where X is over Y and imaginary part the errors where X is under Y.

MRD_bias Is a number bound between -1 and 1. It is 0 iff Y has the same rooted error to the upper as it has to the lower side of X. Positivity means Y deviates more to the lower side of X and conversly negativity reads as Y deviates more the upper side of X.

Value

vector of 'RMSE','MAE','MAPE','SMAPE','MASE','AbsoluteError','Bias','RAE','RSE','MRD','MRD_BIAS'

Author(s)

Michael Thrun

Examples

Y=runif(10)
FOR=runif(10)
QualityMeasuresForecasting(Y,FOR)

Mthrun/TSAT documentation built on Feb. 5, 2024, 11:15 p.m.