# summary.speedglm: Methods to summarize Generalized Linear Models fits In speedglm: Fitting Linear and Generalized Linear Models to Large Data Sets

 summary.speedglm R Documentation

## 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.

Marco ENEA

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.