ATA.Accuracy | R Documentation |
Returns ATA(p,q,phi)(E,T,S) applied to 'ata' object
.
Accuracy measures for a forecast model
Returns range of summary measures of the forecast accuracy. If out.sample
is
provided, the function measures test set forecast accuracy.
If out.sample
is not provided, the function only produces
training set accuracy measures.
The measures calculated are:
lik : maximum likelihood functions
sigma : residual variance.
MAE : mean absolute error.
MSE : mean square error.
RMSE : root mean squared error.
MPE : mean percentage error.
MAPE : mean absolute percentage error.
sMAPE : symmetric mean absolute percentage error.
MASE : mean absolute scaled error.
OWA : overall weighted average of MASE and sMAPE.
MdAE : median absolute error.
MdSE : median square error.
RMdSE : root median squared error.
MdPE : median percentage error.
MdAPE : median absolute percentage error.
sMdAPE : symmetric median absolute percentage error.
ATA.Accuracy(object, out.sample = NULL, print.out = TRUE)
object |
An object of class |
out.sample |
A numeric vector or time series of class |
print.out |
Default is TRUE. If FALSE, summary of ATA Method's accuracy measures is not shown. |
Matrix giving forecast accuracy measures.
Ali Sabri Taylan and Hanife Taylan Selamlar
#'\insertRefhyndmanandkoehler2006ATAforecasting
#'\insertRefhyndman2019forecastingATAforecasting
forecast
, stlplus
, stR
, stl
, decompose
, tbats
, seasadj
.
trainATA <- head(touristTR, 84)
testATA <- window(touristTR, start = 2015, end = 2016.917)
ata_fit <- ATA(trainATA, h=24, seasonal.test = TRUE, seasonal.model = "decomp")
ata_accuracy <- ATA.Accuracy(ata_fit, testATA)
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