logbin (version 1.0)

summary.logbin: Summarizing logbin Model Fits

Description

These functions are all methods for class logbin or summary.logbin objects.

Usage

## S3 method for class 'logbin':
summary(object, correlation = FALSE, ...)

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

Arguments

object

an object of class "logbin", usually from a call to logbin or logbin.smooth.

x

an object of class "summary.logbin", usually from a call to summary.logbin.

correlation

logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.

digits

the number of significant digits to use when printing.

signif.stars

logical; if TRUE, 'significance stars' are printed for each coefficient.

...

further arguments passed to or from other methods.

Value

• summary.logbin returns an object of class "summary.logbin", a list with components
• call
  the component from object.
• family
  the component from object.
• deviance
  the component from object.
• aic
  the component from object.
• aic.c
  the component from object.
• df.residual
  the component from object.
• null.deviance
  the component from object.
• df.null
  the component from object.
• iter
  the component from object.
• deviance.resid
  the deviance residuals: see residuals.glm.
• coefficients
  the matrix of coefficients, standard errors, z-values and p-values.
• aliased
  included for compatability -- always FALSE.
• dispersion
  the inferred/estimated dispersion.
• df
  included for compatability -- a 3-vector of the number of coefficients, the number of residual degrees of freedom, and the number of coefficients (again).
• cov.unscaled
  the unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients. NaN if object$boundary == TRUE.
• cov.scaled
  ditto, scaled by dispersion.
• correlation
  if correlation is TRUE, the estimated correlations of the estimated coefficients. NaN if object$boundary == TRUE.

Details

These perform the same function as summary.glm and print.summary.glm, producing similar results for logbin models. print.summary.logbin additionally prints the small-sample corrected AIC (aic.c), and the number of EM iterations for the parameterization corresponding to the MLE. The dispersion used in calculating standard errors is fixed as 1.

See Also

logbin, summary.glm

Examples

## For examples see example(logbin)