Learn R Programming

tfarima (version 0.4.1)

summary.tfm: Summarize Transfer Function Model

Description

Produces summary statistics for a fitted transfer function model including parameter estimates, standard errors, and diagnostic tests.

Usage

# S3 method for tfm
summary(
  object,
  y = NULL,
  method = c("exact", "cond"),
  digits = max(3L, getOption("digits") - 3L),
  envir = parent.frame(),
  ...
)

Value

Object of class summary.tfm containing: call, coefficient table, variance-covariance matrix, residuals, diagnostic statistics, information criteria, and time series attributes.

Arguments

object

A fitted tfm object.

y

Optional ts object for alternative output series.

method

Character: "exact" or "cond" for residual calculation.

digits

Number of significant digits for printing.

envir

Environment for evaluation. NULL uses calling environment.

...

Additional arguments: p.values (logical) returns only p-values; table (logical) returns only coefficient table.

Details

Computes parameter estimates with standard errors (from Jacobian), z-statistics, p-values, AIC, BIC, log-likelihood, Ljung-Box tests (at lags p+q+1 and n/4+p+q), and Bartlett heteroscedasticity test.

See Also

print.summary.tfm

Examples

Run this code
if (FALSE) {
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))
sm <- summary(tfmy)
print(sm)
}

Run the code above in your browser using DataLab