BoxCox.ts: Box-Cox Analysis for a Time Series
In FitAR: Subset AR Model Fitting

Description Usage Arguments Details Value Warning Note Author(s) References See Also Examples

The time series is converted to a vector and BoxCox.numeric is used.

1 2	## S3 method for class 'ts' BoxCox(object, interval = c(-1, 1), ...)

`object`	a vector of time series values
`interval`	interval to be searched
`...`	optional arguments

For lambda!=0, the Box-Cox transformation is of x is (x^lambda-1)/lambda. If the minimum data value is <= 0, a small positive constant, equal to the negative of the minimum plus 0.25, is added to all the data values.

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

It is important not to transform the data when fitting it with AR since the optimal transformation would be found for the transformed data – not the original data. Normally this would not be a sensible thing to do.

The MASS package has a similar function boxcox but this is implemented only for regression and analysis of variance.

A.I. McLeod

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.

BoxCox.FitAR, BoxCox.Arima, BoxCox.numeric

#
## Not run: #takes a few seconds
BoxCox(sunspot.year)

## End(Not run)

Loading required package: lattice
Loading required package: leaps
Loading required package: ltsa
Loading required package: bestglm
 minimum data value <= 0 so -min+0.25 added to all values