croston

0th

Percentile

Forecasts for intermittent demand using Croston's method

Returns forecasts and other information for Croston's forecasts applied to y.

Keywords
ts
Usage
croston(y, h=10, alpha=0.1, x=y)
Arguments
y
a numeric vector or time series
h
Number of periods for forecasting.
alpha
Value of alpha. Default value is 0.1.
x
Deprecated. Included for backwards compatibility.
Details

Based on Croston's (1972) method for intermittent demand forecasting, also described in Shenstone and Hyndman (2005). Croston's method involves using simple exponential smoothing (SES) on the non-zero elements of the time series and a separate application of SES to the times between non-zero elements of the time series. The smoothing parameters of the two applications of SES are assumed to be equal and are denoted by alpha.

Note that prediction intervals are not computed as Croston's method has no underlying stochastic model. The separate forecasts for the non-zero demands, and for the times between non-zero demands do have prediction intervals based on ETS(A,N,N) models.

Value

An object of class "forecast" is a list containing at least the following elements: is a list containing at least the following elements:The function summary is used to obtain and print a summary of the results, while the function plot produces a plot of the forecasts.The generic accessor functions fitted.values and residuals extract useful features of the value returned by croston and associated functions.

References

Croston, J. (1972) "Forecasting and stock control for intermittent demands", Operational Research Quarterly, 23(3), 289-303.

Shenstone, L., and Hyndman, R.J. (2005) "Stochastic models underlying Croston's method for intermittent demand forecasting". Journal of Forecasting, 24, 389-402.

See Also

ses.

Aliases
  • croston
Examples
fcast <- croston(y)
plot(fcast)
Documentation reproduced from package forecast, version 7.3, License: GPL (>= 2)

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