plots: Plotting functions for HLSM objects

In HLSM: Hierarchical Latent Space Network Model

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.

Author(s)

Sam Adhikari & Tracy Sweet

Examples

#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)

HLSM documentation built on Dec. 11, 2021, 9:43 a.m.