summary.gamlss: gamlss summary

In GJRM: Generalised Joint Regression Modelling

gamlss summary

Description

It takes a fitted gamlss object and produces some summaries from it.

Usage

## S3 method for class 'gamlss'
summary(object, n.sim = 100, prob.lev = 0.05, ...)
   


## S3 method for class 'summary.gamlss'
print(x, digits = max(3, getOption("digits") - 3), 
           signif.stars = getOption("show.signif.stars"), ...)
 

Arguments

object	A fitted gamlss object.
x	summary.gamlss object produced by summary.gamlss().
n.sim	The number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used to calculate intervals for various parameters. 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.
digits	Number of digits printed in output.
signif.stars	By default significance stars are printed alongside output.
...	Other arguments.

Details

print.summary.gamlss prints model term summaries.

Value

tableP1	Table containing parametric estimates, their standard errors, z-values and p-values for equation 1.
tableP2, tableP3	As above but for equations 2 and 3 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 equations 2 and 3.
n	Sample size.
sigma, nu	Estimated distribution specific parameters.
formula1, formula2, formula3	Formulas used for the model equations.
l.sp1, l.sp2, l.sp3	Number of smooth components in model equation.
t.edf	Total degrees of freedom of the estimated bivariate model.
CIsig, CInu	Intervals for distribution specific parameters.

Author(s)

Maintainer: Giampiero Marra [e-mail]

Examples

## see examples for gamlss

GJRM documentation built on Oct. 25, 2024, 5:07 p.m.