forecast (version 7.0)

mforecast: Forecasting time series

Description

mforecast is a class of objects for forecasting from multivariate time series or multivariate time series models. The function invokes particular methods which depend on the class of the first argument.

For example, the function forecast.mlm makes multivariate forecasts based on the results produced by tslm.

Usage

## S3 method for class 'mts':
forecast(object, h=ifelse(frequency(object)>1, 2*frequency(object), 10),
        level=c(80,95), fan=FALSE, robust=FALSE, lambda = NULL, find.frequency = FALSE,
        allow.multiplicative.trend=FALSE, ...)

Arguments

object

a multivariate time series or multivariate time series model for which forecasts are required

h

Number of periods for forecasting

level

Confidence level for prediction intervals.

fan

If TRUE, level is set to seq(51,99,by=3). This is suitable for fan plots.

robust

If TRUE, the function is robust to missing values and outliers in object. This argument is only valid when object is of class mts.

lambda

Box-Cox transformation parameter.

find.frequency

If TRUE, the function determines the appropriate period, if the data is of unknown period.

allow.multiplicative.trend

If TRUE, then ETS models with multiplicative trends are allowed. Otherwise, only additive or no trend ETS models are permitted.

...

Additional arguments affecting the forecasts produced.

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 multivariate forecasts and prediction intervals.

  The generic accessors functions fitted.values and residuals extract various useful features of the value returned by forecast$model.

  An object of class "mforecast" is a list usually 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. For models with additive errors, the residuals will be x minus the fitted values.
• fitted
  Fitted values (one-step forecasts)

See Also

Other functions which return objects of class "mforecast" are forecast.mlm, forecast.varest.