Returns forecasts and prediction intervals for an iid model applied to x.
meanf(x, h=10, level=c(80,95), fan=FALSE, lambda=NULL)
- a numeric vector or time series
- Number of periods for forecasting
- Confidence levels for prediction intervals.
- If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots.
- Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.
The iid model is $$Y_t=\mu + Z_t$$ where $Z_t$ is a normal iid error. Forecasts are given by $$Y_n(h)=\mu$$ where $\mu$ is estimated by the sample mean.
- An object of class "
summaryis used to obtain and print a summary of the results, while the function
plotproduces a plot of the forecasts and prediction intervals.
The generic accessor functions
residualsextract useful features of the value returned by
An object of class
"forecast"is a list containing at least the following elements:
model A list containing information about the fitted model method The name of the forecasting method as a character string mean Point forecasts as a time series lower Lower limits for prediction intervals upper Upper limits for prediction intervals level The confidence values associated with the prediction intervals x The original time series (either
objectitself or the time series used to create the model stored as
residuals Residuals from the fitted model. That is x minus fitted values. fitted Fitted values (one-step forecasts)
nile.fcast <- meanf(Nile, h=10) plot(nile.fcast)