R: Forecast a multiple linear model with possible time series...

forecast.mlm {forecast}

R Documentation

Forecast a multiple linear model with possible time series components

Description

forecast.mlm is used to predict multiple linear models, especially those involving trend and seasonality components.

Usage

## S3 method for class 'mlm'
forecast(object, newdata, h = 10, level = c(80, 95), 
    fan = FALSE, lambda = object$lambda, biasadj = NULL, ts = TRUE, ...)

Arguments

`object`	Object of class "mlm", usually the result of a call to `lm` or `tslm`.
`newdata`	An optional data frame in which to look for variables with which to predict. If omitted, it is assumed that the only variables are trend and season, and `h` forecasts are produced.
`level`	Confidence level for prediction intervals.
`fan`	If `TRUE`, level is set to seq(51,99,by=3). This is suitable for fan plots.
`h`	Number of periods for forecasting. Ignored if `newdata` present.
`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.
`ts`	If `TRUE`, the forecasts will be treated as time series provided the original data is a time series; the `newdata` will be interpreted as related to the subsequent time periods. If `FALSE`, any time series attributes of the original data will be ignored.
`...`	Other arguments passed to `forecast.lm()`.

Details

forecast.mlm is largely a wrapper for forecast.lm() except that it allows forecasts to be generated on multiple series. Also, the output is reformatted into a mforecast object.

Value

An object of class "mforecast".

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 forecast.lm.

An object of class "mforecast" 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 multivariate time series
`lower`	Lower limits for prediction intervals of each series
`upper`	Upper limits for prediction intervals of each series
`level`	The confidence values associated with the prediction intervals
`x`	The historical data for the response variable.
`residuals`	Residuals from the fitted model. That is x minus fitted values.
`fitted`	Fitted values

Author(s)

Mitchell O'Hara-Wild

Examples

lungDeaths <- cbind(mdeaths, fdeaths)
fit <- tslm(lungDeaths ~ trend + season)
fcast <- forecast(fit, h=10)

carPower <- as.matrix(mtcars[,c("qsec","hp")])
carmpg <- mtcars[,"mpg"]
fit <- lm(carPower ~ carmpg)
fcast <- forecast(fit, newdata=data.frame(carmpg=30))

[Package forecast version 8.0 Index]