forecast.mts: Forecasting time series

In forecast: Forecasting Functions for Time Series and Linear Models

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.

Usage

## S3 method for class 'mts'
forecast(
  object,
  h = if (frequency(object) > 1) 2 * frequency(object) else 10,
  level = c(80, 95),
  fan = FALSE,
  robust = FALSE,
  lambda = NULL,
  biasadj = FALSE,
  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. Default value is twice the largest seasonal period (for seasonal data) or ten (for non-seasonal data).
level	Confidence levels 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. 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.
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.

Details

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

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 accessor 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)

Author(s)

Rob J Hyndman & Mitchell O'Hara-Wild

See Also

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

forecast documentation built on March 18, 2026, 9:07 a.m.