# BoxCox.lambda

0th

Percentile

##### Automatic selection of Box Cox transformation parameter

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

Keywords
ts
##### 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.

##### 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

##### Aliases
• BoxCox.lambda
##### Examples
# NOT RUN {
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))

# }

Documentation reproduced from package forecast, version 8.7, License: GPL-3

### Community examples

aiyuyun2010@gmail.com at Aug 22, 2018 forecast v8.4

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))

aiyuyun2010@gmail.com at Aug 22, 2018 forecast v8.4

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))