summary.cmp: Summarizing COM-Poisson Model Fit

In mpcmp: Mean-Parametrized Conway-Maxwell Poisson (COM-Poisson) Regression

Description

summary method for class cmp.

Usage

## S3 method for class 'cmp'
summary(object, ...)

## S3 method for class 'summary.cmp'
print(
  x,
  digits = max(3, getOption("digits") - 3),
  signif.stars = getOption("show.signif.stars"),
  ...
)

Arguments

object	an object class 'cmp', obtained from a call to glm.cmp.
...	other arguments passed to or from other methods (currently unused).
x	a result of the default method of summary().
digits	numeric; minimum number of significant digits to be used for most numbers.
signif.stars	logical. If TRUE, ‘significance stars’ are printed for each coefficient.

Details

print.summary.glm tries to be smart about formatting the coefficients, standard errors and gives 'significance stars'. The coefficients component of the result gives the estimated coefficients and their estimated standard errors, together with their ratio. This third column is labelled as Z value as the dispersion is fixed for this family. A forth column gives the two-tailed p-value corresponding to Z value based on the asymptotic Normal reference distribution.

Value

summary.cmp returns an object of class "summary.cmp", a list containing at least the following components:

call	the component from object.
family	the component from object.
deviance; residual_deviance	the component from object.
df_residual	the component from object.
df_null	the component from object.
null_deviance	the component from object.
deviance_resid	the deviance residuals: see residuals.cmp.
coefficients	the matrix of coefficients, standard errors, z-values and p-values.
df	a 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of coefficients.

See Also

coef.cmp, fitted.cmp, glm.cmp.

Examples

## For examples see example(glm.cmp)

Example output

mpcmp documentation built on Oct. 26, 2020, 9:07 a.m.