fit.tfm: Fit a Transfer Function Model

In tfarima: Transfer Function and ARIMA Models

Fit a Transfer Function Model

Description

Estimates the parameters of a transfer function model of class tfm by (conditional or exact) maximum likelihood.

Usage

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

Arguments

mdl	An object of class tfm created with tfm.
y	Optional ts object containing the output series. If NULL, the output stored in noise is used.
method	Character string specifying likelihood method: "exact" for exact maximum likelihood or "cond" for conditional maximum likelihood. Default is "exact".
optim.method	Character. Optimization method passed to optim. Default is "BFGS". Other options: "Nelder-Mead", "CG", "L-BFGS-B".
show.iter	Logical. If TRUE, prints iteration progress of the likelihood optimization.
fit.noise	Logical. If TRUE (default), the parameters of the noise model are estimated. If FALSE, noise parameters are fixed at their current values.
envir	Environment in which the function arguments are evaluated. If NULL, the calling environment is used.
...	Additional arguments.

Value

An updated object of class tfm containing fitted parameters, estimated innovation variance, and optimization details.

See Also

tfm

Examples

## Not run: 
data(seriesJ)
Y <- seriesJ$Y - mean(seriesJ$Y)
X <- seriesJ$X - mean(seriesJ$X)
umx <- um(X, ar = 3)
umy <- fit(umx, Y)
tfx <- tfest(Y, X, delay = 3, p = 2, q = 2, um.x = umx, um.y = umy)
tfmy <- tfm(Y, inputs = tfx, noise = um(ar = 2), fit = FALSE)
tfmy_fit <- fit(tfmy)

## End(Not run)

tfarima documentation built on Nov. 5, 2025, 7:43 p.m.