meanf: Mean Forecast
In pli2016/forecast: Forecasting Functions for Time Series and Linear Models

Description Usage Arguments Details Value Author(s) See Also Examples

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

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

`y`	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(51,99,by=3). This is suitable for fan plots.
`lambda`	Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.
`biasadj`	Use adjusted back-transformed mean for Box-Cox transformations. If TRUE, point forecasts and fitted values are mean forecast. Otherwise, these points can be considered the median of the forecast densities.
`x`	Deprecated. Included for backwards compatibility.

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 "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:

`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 `object` itself or the time series used to create the model stored as `object`).
`residuals`	Residuals from the fitted model. That is x minus fitted values.
`fitted`	Fitted values (one-step forecasts)