HLSM (version 0.9.0)

HLSMcovplots: Plotting functions for HLSM objects

Description

Functions for plotting HLSM/LSM model fits of class 'HLSM'. HSLMcovplots is the most recent function to plot posterior distribution summaries. HLSMplotLikelihood( ) plots the likelihood, HLSMcovplots( ) summarizes posterior draws of the parameters from MCMC sample, and HLSMplot.fit.LS( ) is for plotting the mean latent position estimates.

Usage

HLSMplotLikelihood(object, burnin = 0, thin = 1)
	HLSMcovplots(fitted.model, burnin = 0, thin = 1)

Arguments

object

object of class 'HLSM' obtained as an output from LSM, HLSMrandomEF() or HLSMfixedEF()

fitted.model

model fit from LSM(), HLSMrandomEF() or HLSMfixedEF()

burnin

numeric value to burn the chain for plotting the results from the 'HLSM'object

thin

a numeric thinning value

Value

returns plot objects.

Examples

# NOT RUN {
#using advice seeking network of teachers in 15 schools
#to fit the data

#Random effect model#
priors = NULL
tune = NULL
initialVals = NULL
niter = 10

random.fit = HLSMrandomEF(Y = ps.advice.mat,FullX = ps.edge.vars.mat,
	initialVals = initialVals,priors = priors,
	tune = tune,tuneIn = FALSE,dd = 2,niter = niter)


HLSMcovplots(random.fit)
# }