BoxCoxlambda: Automatic selection of Box Cox transformation parameter

In pli2016/forecast: Forecasting Functions for Time Series and Linear Models

Description

If method=="guerrero", Guerrero's (1993) method is used, where lambda minimizes the coefficient of variation for subseries of x.

If method=="loglik", the value of lambda is chosen to maximize the profile log likelihood of a linear model fitted to x. For non-seasonal data, a linear time trend is fitted while for seasonal data, a linear time trend with seasonal dummy variables is used.

Usage

BoxCox.lambda(x, method=c("guerrero","loglik"), lower=-1, upper=2)

Arguments

x	a numeric vector or time series
method	Choose method to be used in calculating lambda.
lower	Lower limit for possible lambda values.
upper	Upper limit for possible lambda values.

Value

a number indicating the Box-Cox transformation parameter.

Author(s)

Leanne Chhay and Rob J Hyndman

References

Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations. JRSS B 26 211–246.

Guerrero, V.M. (1993) Time-series analysis supported by power transformations. Journal of Forecasting, 12, 37–48.

See Also

BoxCox

Examples

lambda <- BoxCox.lambda(AirPassengers,lower=0)
air.fit <- Arima(AirPassengers, order=c(0,1,1),
                 seasonal=list(order=c(0,1,1),period=12), lambda=lambda)
plot(forecast(air.fit))

pli2016/forecast documentation built on May 25, 2019, 8:22 a.m.