FitAR (version 1.94)

BoxCox.FitAR: Box-Cox Analysis for "FitAR" Objects

Description

This is a methods function to do a Box-Cox analysis for models fit using FitAR.

Usage

"BoxCox"(object, interval = c(-1, 1), type = "BoxCox", InitLambda = "none", ...)

Arguments

object

output from FitAR

interval

interval to be searched for the optimal transformation

type

Ignored unless, InitLambda!="none". Type of transformation, default is "BoxCox". Otherwise a simple power transformation.

InitLambda

default "none". Otherwise a numerical value giving the transformation parameter.

...

optional arguments passed to optimize

Value

No value returned. Graphical output produced as side-effect. The plot shows relative likelihood function as well as the MLE and a confidence interval.

Details

If no transformation is used on the data, then the original data is used. But if a transformation has already been used, we need to inverse transform the data to recover the untransformed data.

For $lambda!=0$, the Box-Cox transformation is of x is $(x^lambda-1)/lambda$ . If the minimum data value is

References

Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations. Journal of Royal Statistical Society, Series B, vol. 26, pp. 211-246.

McLeod, A.I. and Zhang, Y. (2006a). Partial autocorrelation parameterization for subset autoregression. Journal of Time Series Analysis, 27, 599-612.

McLeod, A.I. and Zhang, Y. (2006b, under review). Subset Autoregression Modelling. Journal of Statistical Sofware.

See Also

BoxCox, BoxCox.Arima

Examples

## Not run:  #takes a few seconds
# #lynx time series. ARp subset model.
# out<-FitAR(lynx, c(1,2,4,10,11), ARModel="ARp")
# BoxCox(out)
# #
# #lynx time series. ARz subset model.
# p<-SelectModel(lynx, ARModel="ARz", lag.max=25, Best=1)
# out<-FitAR(lynx, p)
# BoxCox(out)
# ## End(Not run)