R: Summarizing Output of an EM Algorithm by the Method of...

summary.icdglm {icdGLM}

R Documentation

Summarizing Output of an EM Algorithm by the Method of Weights Using GLMs

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

## S3 method for class 'icdglm'
summary(object, dispersion = NULL, correlation = FALSE, symbolic.cor = FALSE, ...)

`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.

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.

The description of this function is taken from summary.glm apart from a few differences.