gwer (version 1.0)

summary.elliptical: Summarizing Elliptical Model Fits.

Description

These functions are all methods for class glm or summary.glm objects.

Usage

# S3 method for elliptical
summary(object, correlation = TRUE, ...)

Arguments

object

fit object for elliptical regression model.

correlation

if TRUE, the correlation matrix of the estimated parameters is returned and printed.

...

arguments to be used to form the default control argument if it is not supplied directly.

Value

returns an object of class summary.elliptical, a list with components:

coefficients

the matrix of coefficients, standard errors and significance values for hypothesis test.

dispersion

either the supplied argument or the estimated dispersion with standard error.

residuals

residuals from object.

cov.unscaled

the unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients.

corrrelation

the likelihood logarithm value of the adjusted model's.

family

family from object.

loglik

logarithmic likelihood from object.

terms

the terms object used.

df

degrees of fredom from object.

inter

the number of iterations of optimization process from object.

nas

a logical vector indicating if there is na in estimation of coefficients.

call

the matched call from object.

scale

the values of the 4d_g for the specified distribution from object.

scaledispersion

the values of the 4f_g for the specified distribution from object.

References

Cysneiros, F. J. A., Paula, G. A., and Galea, M. (2007). Heteroscedastic symmetrical linear models. Statistics & probability letters, 77(11), 1084-1090. https://doi.org/10.1016/j.spl.2007.01.012

See Also

glm, elliptical, elliptical.diag

Examples

# NOT RUN {
data(luzdat)
y <- luzdat$y
x1 <- luzdat$x1 ; x1 <- factor(x1) ; x1 <- C(x1,treatment)
x2 <- luzdat$x2
x3 <- (luzdat$x2)^2
luz <- data.frame(y,x1,x2,x3)
elliptical.fitt <- elliptical(y ~ x1+x2+x3, family = Student(df=5)
,data=luz)
summary(elliptical.fitt)
# }