summary.lmp: Summarize linear model fits with exponential power...

In normalp: Routines for Exponential Power Distribution

Description

This function is the summary method for class "lmp". This function produces a set of results for a linear regression model. By assuming that in a linear regression model the errors are distributed as an exponential power distribution, we can use the function lmp.

Usage

## S3 method for class 'lmp'
summary(object, ...)
## S3 method for class 'summary.lmp'
print(x, ...)

Arguments

object	An object of class "lmp", a result of a call to lmp.
x	An object of class "summary.lmp".
...	Further arguments passed to or from other methods.

Value

The function summary returns a list of summary statistics of the fitted linear model given in lmp, using the components (list elements) call and terms from its argument, plus

Call	The matched call.
Residuals	A summary of the vector of residuals e[i].
Coefficients	Vector of coefficients.
Estimate of p	An estimate of the shape parameter p.
Power deviation of order p	The power deviation of order p given by Sp = (1/(n-p) Sum(e[i]^p))^1/p where q is either the number of the estimated regression coefficients if p is known, either the number of the estimated regression coefficients plus 1 if p is estimated.

Author(s)

Angelo M. Mineo

Examples

x<-runif(30)
e<-rnormp(30,0,3,1.25)
y<-0.5+x+e
L<-lmp(y~x)
summary(L)

Example output

Call:
lmp(formula = y ~ x)

Residuals:
    Min      1Q  Median      3Q     Max 
-6.4296 -2.1293  0.9105  2.4370  5.6320 

Coefficients:
(Intercept)           x 
     0.4011      1.4835 

Estimate of p
`3.376549`

Power deviation of order p: 3.601

normalp documentation built on Feb. 14, 2020, 5:08 p.m.