summary.speedlm: Methods to summarize Linear Models fits

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

Methods to summarize Linear Models fits

Description

summary method for class 'speedlm'.

Usage

## S3 method for class 'speedlm'
summary(object, correlation = FALSE,...)
## S3 method for class 'speedlm'
coef(object,...)
## S3 method for class 'speedlm'
vcov(object,...)
## S3 method for class 'speedlm'
logLik(object,...)
## S3 method for class 'speedlm'
AIC(object,...,k = 2)

Arguments

object	an object of class 'speedlm'.
correlation	logical. Do you want to print the correlation matrix? By default it is false.
k	numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.
...	further optional arguments

Value

coefficients	the matrix of coefficients, standard errors, t-statistics and two-side p-values.
rdf	degrees of freedom of the fitted model. It is a component from object.
call	the component from object.
r.squared	R^2, the fraction of variance explained by the model.
adj.r.squared	the "adjusted" R^2 statistic, penalizing for higher p.
fstatistic	(for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
f.pvalue	p-value of the F-statistic.
RSS	Residual sum of squares.
var.res	estimated variance of residuals.
rank	the component from object.
correlation	(only if correlation is true) the correlations of the estimated parameters.
...	the results from the functions logLik, AIC and vcov.

Author(s)

Marco ENEA

See Also

speedlm

Examples

data(data1)
m <- speedlm(y ~ x1 + x2 + factor(fat1), data1)
summary(m)

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