croston | R Documentation |
Returns forecasts and other information for Croston's forecasts applied to y.
croston(y, h = 10, alpha = 0.1, x = y)
y |
a numeric vector or time series of class |
h |
Number of periods for forecasting. |
alpha |
Value of alpha. Default value is 0.1. |
x |
Deprecated. Included for backwards compatibility. |
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 model used for non-zero demands.
The second element gives the model used for times between non-zero demands.
Both elements 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 y 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
.
y <- rpois(20,lambda=.3)
fcast <- croston(y)
plot(fcast)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.