| croston {forecast} | R Documentation |
Returns forecasts and other information for Croston's forecasts applied to x.
croston(x, h=10, alpha=0.1)
x |
a numeric vector or time series |
h |
Number of periods for forecasting. |
alpha |
Value of alpha. Default value is 0.1. |
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.
An object of class "forecast" is a list containing at least the following elements:
model |
A list containing information about the fitted model. The first element gives the SES model used for non-zero demands.
The second element gives the SES model used for times between non-zero demands. Both models are of class |
method |
The name of the forecasting method as a character string |
mean |
Point forecasts as a time series |
x |
The original time series (either |
residuals |
Residuals from the fitted model. That is x minus fitted values. |
fitted |
Fitted values (one-step forecasts) |
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.
Rob J Hyndman
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.
ses.
x <- rpois(20,lambda=.3) fcast <- croston(x) plot(fcast)