# BoxCox.lambda: Automatic selection of Box Cox transformation parameter In forecast: Forecasting Functions for Time Series and Linear Models

 BoxCox.lambda R Documentation

## 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.

`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 July 25, 2022, 5:05 p.m.