predict.tfm: Forecasting with transfer function models

In tfarima: Transfer Function and ARIMA Models

Forecasting with transfer function models

Description

predict computes point and interval predictions for a time series based on a tfm object.

Usage

## S3 method for class 'tfm'
predict(
  object,
  newdata = NULL,
  y = NULL,
  ori = NULL,
  n.ahead = NULL,
  level = 0.95,
  i = NULL,
  envir = NULL,
  ...
)

Arguments

object	an object of class um.
newdata	new data for the predictors for the forecast period. This is a matrix if there is more than one predictor. The number of columns is equal to the number of predictors, the number of rows equal to n.ahead. If there is one predictor only the data may be provided alternatively as a vector.
y	an object of class ts.
ori	the origin of prediction. By default, it is the last observation.
n.ahead	number of steps ahead.
level	confidence level.
i	transformation of the series y to be forecasted. It is a lagpol as those of a um object.
envir	environment in which the function arguments are evaluated. If NULL the calling environment of this function will be used.
...	additional arguments.

Details

Forecasts for the inputs of a tfm object can be provided in tree ways: (1) extending the time series with forecasts so that the length of the intput is greater than the length of the output, (2) computed internally from the um object associated to the input and (3) with the newdata argument.

tfarima documentation built on May 20, 2022, 5:06 p.m.