meanf: Mean Forecast

In forecast: Forecasting Functions for Time Series and Linear Models

Mean Forecast

Description

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

Usage

meanf(
  y,
  h = 10,
  level = c(80, 95),
  fan = FALSE,
  lambda = NULL,
  biasadj = FALSE,
  bootstrap = FALSE,
  npaths = 5000,
  x = y
)

Arguments

y	a numeric vector or time series of class ts
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. If lambda="auto", then a transformation is automatically selected using BoxCox.lambda. The transformation is ignored if NULL. Otherwise, data transformed before model is estimated.
biasadj	Use adjusted back-transformed mean for Box-Cox transformations. If transformed data is used to produce forecasts and fitted values, a regular back transformation will result in median forecasts. If biasadj is TRUE, an adjustment will be made to produce mean forecasts and fitted values.
bootstrap	If TRUE, use a bootstrap method to compute prediction intervals. Otherwise, assume a normal distribution.
npaths	Number of bootstrapped sample paths to use if bootstrap==TRUE.
x	Deprecated. Included for backwards compatibility.

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.

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:

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)

Author(s)

Rob J Hyndman

See Also

rwf

Examples

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

forecast documentation built on June 22, 2024, 9:20 a.m.