accuracy: Error measures for an estimated model

In greybox: Toolbox for Model Building and Forecasting

Error measures for an estimated model

Description

Function produces error measures for the provided object and the holdout values of the response variable. Note that instead of parameters x, test, the function accepts the vector of values in holdout. Also, the parameters d and D are not supported - MASE is always calculated via division by first differences.

Usage

## S3 method for class 'greybox'
accuracy(object, holdout = NULL, ...)

## S3 method for class 'predict.greybox'
accuracy(object, holdout = NULL, ...)

Arguments

object	The estimated model or a forecast from the estimated model generated via either predict() or forecast() functions.
holdout	The vector of values of the response variable in the holdout (test) set. If not provided, then the function will return the in-sample error measures.
...	Other variables passed to the forecast() function (e.g. newdata).

Details

The function is a wrapper for the measures function and is implemented for convenience.

Author(s)

Ivan Svetunkov, [e-mail]

Examples

xreg <- cbind(rlaplace(100,10,3),rnorm(100,50,5))
xreg <- cbind(100+0.5*xreg[,1]-0.75*xreg[,2]+rlaplace(100,0,3),xreg,rnorm(100,300,10))
colnames(xreg) <- c("y","x1","x2","Noise")

ourModel <- alm(y~x1+x2+trend, xreg, subset=c(1:80), distribution="dlaplace")
predict(ourModel,xreg[-c(1:80),]) |>
   accuracy(xreg[-c(1:80),"y"])

greybox documentation built on Sept. 16, 2023, 9:07 a.m.