BoxCox.lambda: Automatic selection of Box Cox transformation parameter

In forecast: Forecasting Functions for Time Series and Linear Models

Automatic selection of Box Cox transformation parameter

Description

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

Usage

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

Arguments

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

Details

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.

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))

forecast documentation built on Aug. 31, 2023, 5:13 p.m.