tsum {hett}R Documentation

Summary function for the scale or location component of a heteroscedastic t model

Description

Summarizes the location or scale components of a heteroscedastic t model

Usage


tsum(object, dispersion = NULL, correlation = FALSE,
             symbolic.cor = FALSE, ...)

## S3 method for class 'tsum':
print(x, digits = max(3, getOption("digits") - 3), symbolic.cor =
      x$symbolic.cor, signif.stars = getOption("show.signif.stars"),
      scale = TRUE, ...)

Arguments

object either the location or scale object created by fitting a heteroscedastic t object with tlm
x an object of class "tsum"
dispersion 1 if summarizing the location model; 2 if summarizing the scale model (see Details)
correlation logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
digits the number of significant digits to be printed.
symbolic.cor logical. If TRUE, print the correlations in a symbolic form (see `symnum') rather than as numbers.
signif.stars logical. if TRUE, "significance stars" are printed for each coefficient.
scale logical. If TRUE then the dispersion is known in advance (2), and is printed accordingly.
... further arguments passed to or from other methods.

Details

The argument supplied to dispersion must be either 1 (location model) or 2 (scale model). The reason for this is because the fitting of the model has already scaled the covariance matrix for the location coefficients. Hence the scaled and unscaled versions of covariance matrix for the location model are identical.

This function will not be generally called by the user as it will only summarize the location or scale model but not both. Instead the user should refer to summary.tlm to print a summary of both models.

Value

tsum returns an object of class "tsum", a list with components

call the component from object
df.residual the component from object
coefficients the matrix of coefficients, standard errors, z-values and p-values
dispersion the supplied dispersion argument
df a 2-vector of the rank of the model and the number of residual degrees of freedom
cov.unscaled the unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients
cov.scaled ditto, scaled by dispersion
correlation (only if correlation is true.) The estimated correlations of the estimated coefficients
symbolic.cor (only if correlation is true.) The value of the argument symbolic.cor

Author(s)

Julian Taylor

See Also

summary.tlm, tlm

Examples


data(mm, package = "hett")
attach(mm)
tfit <- tlm(m.marietta ~ CRSP, ~ CRSP, data = mm, start = list(dof = 3),
estDof = TRUE) 
tsum(tfit$loc.fit, dispersion = 1) 

[Package hett version 0.3 Index]