crost.ma: Moving average with Croston's method decomposition

In tsintermittent: Intermittent Time Series Forecasting

Moving average with Croston's method decomposition

Description

Moving average with Croston's method decomposition for intermittent demand series with fixed or optimised parameters.

Usage

crost.ma(data,h=10,w=NULL,nop=c(2,1),type=c("croston","sba","sbj"),
         cost=c("mar","msr","mae","mse"),outplot=c(FALSE,TRUE),
         na.rm=c(FALSE,TRUE))

Arguments

data	Intermittent demand time series.
h	Forecast horizon.
w	Moving average order. If w == NULL then moving average orders are optimised. If w is a single value then the same order is used for smoothing both the demand and the intervals. If two values are provided then the second is used to smooth the intervals.
nop	Specifies the number of model parameters. Used only if they are optimised. 1. 1 - Demand and interval moving average order are the same; 2. 2 - Different demand and interval orders.
type	Croston's method variant: 1. "croston" Croston's method; 2. "sba" Syntetos-Boylan approximation; 3. "sbj" Shale-Boylan-Johnston.
cost	Cost function used for optimisation: 1. "mar" - Mean Absolute Rate; 2. "msr" - Mean Squared Rate; 3. "mae" - Mean Absolute Error; 4. "mse" - Mean Squared Error.
outplot	If TRUE a plot of the forecast is provided.
na.rm	A logical value indicating whether NA values should be remove using the method.

Value

model	Type of model fitted.
frc.in	In-sample demand rate.
frc.out	Out-of-sample demand rate.
order	Moving averages orders for demand and interval.
component	List of c.in and c.out containing the non-zero demand and interval vectors for in- and out-of-sample respectively. Third element is the coefficient used to scale demand rate for sba and sbj.

Author(s)

Nikolaos Kourentzes

References

Optimisation cost functions described in: N. Kourentzes, 2014, On intermittent demand model optimisation and selection, International Journal of Production Economics, 156: 180-190. doi: 10.1016/j.ijpe.2014.06.007.

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

See Also

crost, tsb, sexsm.

Examples

crost.ma(ts.data1,outplot=TRUE)

tsintermittent documentation built on July 18, 2022, 9:06 a.m.