forecast.mlm is used to predict multiple linear models, especially
those involving trend and seasonality components.
# S3 method for mlm forecast(object, newdata, h = 10, level = c(80, 95), fan = FALSE, lambda = object$lambda, biasadj = NULL, ts = TRUE, ...)
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
Number of periods for forecasting. Ignored if
Confidence level for prediction intervals.
Box-Cox transformation parameter. Ignored if
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.
Other arguments passed to
An object of class "
summary is used to obtain and print a summary of the
results, while the function
plot produces a plot of the forecasts and
The generic accessor functions
extract useful features of the value returned by
An object of class
"mforecast" is a list containing at least the
A list containing information about the fitted model
The name of the forecasting method as a character string
Point forecasts as a multivariate time series
Lower limits for prediction intervals of each series
Upper limits for prediction intervals of each series
The confidence values associated with the prediction intervals
The historical data for the response variable.
Residuals from the fitted model. That is x minus fitted values.
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