fit function

Estimation of the ARIMA model

fit fits the univariate model to the time series z.

## S3 method for class 'tfm'
fit(
  mdl,
  y = NULL,
  method = c("exact", "cond"),
  optim.method = "BFGS",
  show.iter = FALSE,
  fit.noise = TRUE,
  envir = NULL,
  ...
)

fit(mdl, ...)

## S3 method for class 'um'
fit(
  mdl,
  z = NULL,
  method = c("exact", "cond"),
  optim.method = "BFGS",
  show.iter = FALSE,
  envir = NULL,
  ...
)

Arguments

• mdl: an object of class um or tfm.

• y: a ts object.

• method: Exact/conditional maximum likelihood.

• optim.method: the method argument of the optim

  function.

• show.iter: logical value to show or hide the estimates at the different iterations.

• fit.noise: logical. If TRUE parameters of the noise model are fixed.

• envir: environment in which the function arguments are evaluated. If NULL the calling environment of this function will be used.

• ...: additional arguments.

• z: a time series.

Returns

A tfm object.

An object of class "um" with the estimated parameters.

Note

The um function estimates the corresponding ARIMA model when a time series is provided. The fit function is useful to fit a model to several time series, for example, in a Monte Carlo study.

Examples

z <- AirPassengers
airl <- um(i = list(1, c(1, 12)), ma = list(1, c(1, 12)), bc = TRUE)
airl <- fit(airl, z)