R: Methods to summarize Linear Models fits

summary.speedlm {speedglm} | R Documentation

## 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

    y <- rnorm(100,1.5,1)
    x <- round(matrix(rnorm(200), 100, 2), digits = 3)
    colnames(x) <- c("s1","s2")
    da <- data.frame(y, x)

    m <- speedlm(y ~ s1 + s2,da)
    summary(m)

[Package speedglm version 0.3-2 Index]