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glarma (version 1.4-0)

summary.glarma: Summarize GLARMA Fit

Description

summary method for class glarma and functions to generate the estimates for this summary method.

Usage

"summary"(object, tests = TRUE, ...) "print"(x, digits = max(3L, getOption("digits") - 3L), ...) glarmaModelEstimates(object)

Arguments

object
An object of class "glarma", obtained from a call to glarma.
x
An object of class "summary.glarma", obtained from a call to summary.glarma.
digits
Numeric; minimum number of significant digits to be used for most numbers.
tests
Logical; if TRUE, the likelihood-ratio test and the Wald test are shown in the summary. The default is TRUE.
...
Further arguments passed to or from other methods.

Value

summary.glarma returns an object of class "summary.glarma", a list with components
call
the component from object
null.deviance
null deviance of the GLM with the same regression structure as the GLARMA model.
df.null
null degrees of freedom of the GLM with the same regression structure as the GLARMA model.
phi.lags
the component from object.
theta.lags
the component from object.
pq
the component from object.
iter
the component from object.
deviance
the deviance of the fitted model.
df.residual
the degrees of freedom of the fitted model.
deviance.resid
the component from object.
aic
the component from object.
methods
vector specifying the count distribution of the GLARMA model, the iteration method and the type of residual used.
tests
whether tests were asked for.
likTests
if tests is TRUE, the result of a call to likTests, NULL otherwise.
coefficients1
the matrix of beta coefficients, standard errors, z-ratio and p-values.
coefficients2
the matrix of ARMA coefficients, standard errors, z-ratio and p-values.
coefficients3
when the count distribution is negative binomial, a matrix with 1 row, giving the negative binomial parameter, its standard error, z-ratio and p-value.

See Also

glarma, summary.

Examples

Run this code
## For examples see example(glarma)

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