tsintermittent (version 1.9)

data.frc: Wrapper to forecasts data.frames with a single call

Description

Wrapper to forecasts data.frames with a single call.

Usage

data.frc(data.in,method=c("crost","crost.ma","tsb","sexsm","imapa","auto"),...)

Arguments

data.in

Data frame with time series. This can also be a matrix or array with each column being a different time series.

method

Which method to use for forecasting: "crost", "crost.ma", "tsb", "sexsm", "imapa", "auto". "auto" uses PKa classification to select automatically between Croston, SBA and SES.

...

Additional inputs to pass to forecasting functions. See individual function documentation for options.

Value

frc.out

Data frame containing forecasts for all time series.

out

List with detailed output per series. To access individual outputs of the list use: sapply(out, get, x="element"), where "element" could be for example "frc.in".

References

By default methods are optimised using the cost functions introduced by: N. Kourentzes, 2014, On intermittent demand model optimisation and selection, International Journal of Production Economics, 156: 180-190. http://dx.doi.org/10.1016/j.ijpe.2014.06.007.

http://kourentzes.com/forecasting/2014/06/11/on-intermittent-demand-model-optimisation-and-selection/

The PK approximate classification is described in: F. Petropoulos and N. Kourentzes, 2015, Journal of Operational Research Society. http://www.palgrave-journals.com/jors/journal/v66/n6/full/jors201462a.html. http://kourentzes.com/forecasting/2014/05/13/forecast-combinations-for-intermittent-demand/

See Also

crost, crost.ma, tsb, sexsm, imapa, idclass.

Examples

data.frc(simID(10,30),method="crost",type="sba",h=5)$frc.out