Learn R Programming
icdGLM (version 1.0.0)

summary.icdglm: Summarizing Output of an EM Algorithm by the Method of Weights Using GLMs

Description

This function gives a summary of the output of icdglm. summary.icdglm inherits from summary.glm.

Usage

"summary"(object, dispersion = NULL, correlation = FALSE, symbolic.cor = FALSE, ...)

Arguments

object
an object of class "icdglm", usually, a result of a call to icdglm.
dispersion
the dispersion parameter for the family used. Either a single numerical value or NULL (the default), when it is inferred from object (see details of summary.glm).
correlation
logical, if TRUE, the correlation matrix of the estimated parameters is returned and printed.
symbolic.cor
logical, if TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers.
...
further arguments passed to or from other methods.

Value

summary.icdglm returns an object of class "summary.icdglm", a list with components:
  • callfunction call of object
  • termsthe terms object used.
  • familythe component from object
  • deviancethe component from object
  • aicthe component from object
  • df.residualthe residual degrees of freedom of the initial data set
  • null.deviancethe component from object
  • df.nullthe residual degrees of freedom for the null model.
  • iterthe number of iterations in icdglm.fit, component from object
  • deviance.residthe deviance residuals: see residuals.glm
  • coefficientsthe matrix of coefficients, (corrected) standard errors, t-values and p-values.
  • aliasednamed logical vector showing if the original coefficients are aliased.
  • dispersioneither the supplied argument or the inferred/estimated dispersion if the latter is NULL.
  • dfa 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of coefficients (including aliased ones).
  • cov.unscaledthe unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients.
  • cov.scaledditto, scaled by dispersion
  • correlation(only if correlation is TRUE) The estimated correlations of the estimated coefficients.
  • symbolic.cor(only if correlation is TRUE) The value of the argument symbolic.cor.

See Also

icdglm, summary.glm, summary, glm