forecast (version 3.00)

meanf: Mean Forecast

Description

Returns forecasts and prediction intervals for an iid model applied to x.

Usage

meanf(x, h=10, level=c(80,95), fan=FALSE, lambda=NULL)

Arguments

x
a numeric vector or time series
h
Number of periods for forecasting
level
Confidence levels for prediction intervals.
fan
If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots.
lambda
Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.

Value

  • An object of class "forecast". The function summary is used to obtain and print a summary of the results, while the function plot produces a plot of the forecasts and prediction intervals. The generic accessor functions fitted.values and residuals extract useful features of the value returned by meanf. An object of class "forecast" is a list containing at least the following elements:
  • modelA list containing information about the fitted model
  • methodThe name of the forecasting method as a character string
  • meanPoint forecasts as a time series
  • lowerLower limits for prediction intervals
  • upperUpper limits for prediction intervals
  • levelThe confidence values associated with the prediction intervals
  • xThe original time series (either object itself or the time series used to create the model stored as object).
  • residualsResiduals from the fitted model. That is x minus fitted values.
  • fittedFitted values (one-step forecasts)

Details

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.

See Also

rwf

Examples

Run this code
nile.fcast <- meanf(Nile, h=10)
plot(nile.fcast)

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