forecast (version 3.14)

bats: BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)

Description

Fits a BATS model applied to y.

Usage

bats(y, use.box.cox=NULL, use.trend=NULL, use.damped.trend=NULL, 
  seasonal.periods=NULL, use.arma.errors=TRUE, ...)

Arguments

y

The time series to be forecast. Can be numeric, msts or ts. Only univariate time series is supported.

use.box.cox

TRUE/FALSE indicates whether to use the Box-Cox transformation or not. If NULL then both are tried and the best fit is selected by AIC.

use.trend

TRUE/FALSE indicates whether to include a trend or not. If NULL then both are tried and the best fit is selected by AIC.

use.damped.trend

TRUE/FALSE indicates whether to include a damping parameter in the trend or not. If NULL then both are tried and the best fit is selected by AIC.

seasonal.periods

If y is a numeric then seasonal periods can be specified with this parameter.

use.arma.errors

TRUE/FALSE indicates whether to include ARMA errors or not. If NULL then both are tried and the best fit is selected by AIC.

...

Additional parameters to be passed to auto.arima when choose an ARMA(p, q) model for the errors.

Value

• An object of class "bats". The generic accessor functions fitted.values and residuals extract useful features of the value returned by ets and associated functions.

References

De Livera, A.M., Hyndman, R.J., & Snyder, R. D. (2012), Forecasting time series with complex seasonal patterns using exponential smoothing, Journal of the American Statistical Association, to appear.

Examples

fit <- bats(USAccDeaths)
plot(forecast(fit))
taylor.fit <- bats(taylor)
plot(forecast(taylor.fit))