summary.speedglm: Methods to summarize Generalized Linear Models fits

In speedglm: Fitting Linear and Generalized Linear Models to Large Data Sets

Methods to summarize Generalized Linear Models fits

Description

summary method for the class 'speedglm'.

Usage

## S3 method for class 'speedglm'
summary(object,correlation=FALSE,...)
## S3 method for class 'speedglm'
coef(object,...)
## S3 method for class 'speedglm'
vcov(object,...)
## S3 method for class 'speedglm'
logLik(object,...)
## S3 method for class 'speedglm'
AIC(object,...)

Arguments

object	an object of class 'speedglm'.
correlation	logical. Do you want to print the correlation matrix? By default it is false.
...	further optional arguments

Value

coefficients	the matrix of coefficients, standard errors, z-statistics and two-side p-values.
df.residual	the component from object.
df.null	the component from object.
null.deviance	the component from object.
deviance	the component from object.
family	the component from object.
call	the component from object.
AIC	the Akaike Information Criterion.
RSS	Residuals sums of squares.
correlation	(only if correlation is true.) The correlations of the estimated coefficients.
logLik	the log-likelihood value.
rank	the component from object.
dispersion	the estimated dispersion parameter of the fitted model.
convergence	the component from object.
iter	the component from object.
tol	the component from object.

Author(s)

Marco ENEA

See Also

speedglm

Examples

data(data1)
mod <- speedglm(y~x1+x2+factor(fat1), data=data1, family=Gamma(log))
summary(mod)

speedglm documentation built on May 31, 2023, 7:58 p.m.