`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.

# S3 method for 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:

modelA list containing information about the
fitted model

methodThe name of the forecasting method as a
character string

meanPoint forecasts as a time series

lowerLower limits for prediction intervals

upperUpper
limits for prediction intervals

levelThe confidence values
associated with the prediction intervals

xThe original time series
(either `object`

itself or the time series used to create the model
stored as `object`

).

residualsResiduals from the fitted model.
For models with additive errors, the residuals will be x minus the fitted
values.

fittedFitted values (one-step forecasts)

## Details

For example, the function `forecast.mlm`

makes multivariate
forecasts based on the results produced by `tslm`

.

## See also

Other functions which return objects of class `"mforecast"`

are `forecast.mlm`

, `forecast.varest`

.