summary.marg {marg}

Summary Method for Objects of Class “marg”

Description

Returns a summary list for objects of class marg.

Usage

## S3 method for class 'marg'
summary(object, alpha = 0.05, test = NULL, all = FALSE, 
        coef = TRUE, int = ifelse((is.null(test) || all), TRUE, FALSE), 
        digits = NULL, ...)

Arguments

object

a marg object. This is assumed to be the result returned by the cond.rsm function.

alpha

a vector of levels for confidence intervals; the default is 5%.

test

a vector of values of the parameter of interest one wants to test for. If NULL no test is performed. The default is NULL.

all

logical value; if TRUE all the information stored in the summary.marg object is printed, else only a subset of it. The default is FALSE.

coef

logical value; if TRUE the unconditional and approximate conditional/marginal MLEs are printed. The default is TRUE.

int

logical value; if TRUE confidence intervals are printed. The default is TRUE.

digits

the number of significant digits to be printed. The default depends on the value of digits set by options

...

absorbs any additional argument.

Details

This function is a method for the generic function summary() for objects of class marg. It can be invoked by calling summary or directly summary.marg for an object of the appropriate class.

Value

A list is returned with the following components:

coefficients

a 2\times 2 matrix containing the unconditional and approximate conditional/marginal MLEs and their standard errors.

conf.int

a matrix containing, for each level given in alpha, the upper and lower confidence bounds derived from several first and higher order test statistics. One-sided and two-sided confidence intervals are considered. See marg.object for details on the test statistics used.

signif.tests

a list with two elements. The first (stats) contains, for each value given in test, the values and tail probabilities of several first and higher order test statistics. See marg.object for details on the test statistics. The second element of the list (qTerm) contains for each tested hypothesis the correction term used in the higher order solutions.

call

the function call that created the marg object.

formula

the model formula.

family

the name of the error distribution.

offset

the covariate occurring in the model formula whose coefficient represents the parameter of interest or scale if the parameter of interest is the scale parameter.

alpha

the vector of levels used to compute the confidence intervals.

hypotheses

the values for the parameter of interest that have been tested for.

diagnostics

the information and nuisance parameters aspects; see marg.object for details.

n.approx

the number of output points that have been calculated exactly.

all

logical value; if TRUE, all the information stored in the summary.marg object is printed.

cf

logical value; if TRUE, the parameter estimates are printed.

int

logical value; if TRUE, confidence intervals are printed.

is.scalar

a logical value indicating whether there are any nuisance parameters. If FALSE there are none.

digits

the number of significant digits to be printed.

Note

If the parameter of interest is the scale parameter, all calculations are performed on the log scale, though most results are reported on the original scale.

The amount of information calculated may vary depending on whether there are any nuisance parameters. A message is printed if there are none.

See Also

summary, marg.object

Examples

## House Price Data
data(houses)
houses.rsm <- rsm(price ~ ., family = student(5), data = houses)
houses.marg <- cond(houses.rsm, floor)
summary(houses.marg, test = 0, coef = FALSE)