R: BATS model (Exponential smoothing state space model with...

bats {forecast}

R Documentation

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, as described in De Livera, Hyndman & Snyder (2011). Parallel processing is used by default to speed up the computatons.

Usage

bats(y, use.box.cox=NULL, use.trend=NULL, use.damped.trend=NULL, 
  seasonal.periods=NULL, use.arma.errors=TRUE, use.parallel=TRUE, num.cores=NULL, bc.lower=0, bc.upper=1, ...)

Arguments

`y`	The time series to be forecast. Can be `numeric`, `msts` or `ts`. Only univariate time series are 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 `TRUE` the best fit is selected by AIC. If `FALSE` then the selection algorithm does not consider ARMA errors.
`use.parallel`	`TRUE/FALSE` indicates whether or not to use parallel processing.
`num.cores`	The number of parallel processes to be used if using parallel processing. If `NULL` then the number of logical cores is detected.
`bc.lower`	The lower limit (inclusive) for the Box-Cox transformation.
`bc.upper`	The upper limit (inclusive) for the Box-Cox transformation.
`...`	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 bats and associated functions.

Author(s)

Slava Razbash and Rob J Hyndman

References

De Livera, A.M., Hyndman, R.J., & Snyder, R. D. (2011), Forecasting time series with complex seasonal patterns using exponential smoothing, Journal of the American Statistical Association, 106(496), 1513-1527.

Examples

fit <- bats(USAccDeaths)
plot(forecast(fit))
## Not run: 
taylor.fit <- bats(taylor)
plot(forecast(taylor.fit))

## End(Not run)

[Package forecast version 3.24 Index]