summary.copulaReg: copulaReg summary

Description

It takes a fitted copulaReg object produced by copulaReg() and produces some summaries from it.

Usage

"summary"(object, n.sim = 100, prob.lev = 0.05, cm.plot = FALSE,  ylab = "Margin 2", xlab = "Margin 1", n.grid = 1000, n.dig = 2, ...) 

"print"(x, digits = max(3, getOption("digits") - 3),  signif.stars = getOption("show.signif.stars"), ...)

Arguments

object

A fitted copulaReg object as produced by copulaReg().

summary.copulaReg object produced by summary.copulaReg().

n.sim

The number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used to calculate intervals for the association parameter, dispersion coefficient etc. It may be increased if more precision is required.

prob.lev

Probability of the left and right tails of the posterior distribution used for interval calculations.

cm.plot

If TRUE then a filled bivariate contour meta plot corresponding to the assumed (estimated) bivariate model is produced.

xlab, ylab

Margin labels.

n.grid

Number of grid points used in contour plot construction. This is relevant for continuous margins.

n.dig

Number of digit points used in rounding bivariate pdf values for contour plot construction. This is relevant for continuous margins.

digits

Number of digits printed in output.

signif.stars

By default significance stars are printed alongside output.

...

Other graphics parameters to pass on to plotting commands. These are used only when cm.plot=TRUE.

Value

tableP1: Table containing parametric estimates, their standard errors, z-values and p-values for equation 1.
tableP2,tableP3, ...: As above but for equation 2 and equations 3 and 4 if present.
tableNP1: Table of nonparametric summaries for each smooth component including effective degrees of freedom, estimated rank, approximate Wald statistic for testing the null hypothesis that the smooth term is zero and corresponding p-value, for equation 1.
tableNP2,tableNP3, ...: As above but for equation 2 and equations 3 and 4 if present.
n: Sample size.
theta: Estimated dependence parameter linking the two equations.
sigma21,sigma22: Estimated distribution specific parameters for equations 1 and 2.
nu1,nu2: Estimated distribution specific parameters for equations 1 and 2.
formula1,formula2,formula3, ...: Formulas used for the model equations.
l.sp1,l.sp2,l.sp3, ...: Number of smooth components in model equations.
t.edf: Total degrees of freedom of the estimated bivariate model.
CItheta: Interval(s) for $\theta$.
CIsig21,CIsig22,CInu1,CInu2: Intervals for distribution specific parameters

Details

This function is very similar to summary.SemiParBIVProbit().

print.summary.copulaReg prints model term summaries.

Examples

Run this code

## see examples for copulaReg

Run the code above in your browser using DataLab