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Tip revision: 31ec11bc3c0ac504839d98ce0e6e8feb8951fbbe authored by Samrachana Adhikari on 18 June 2014, 00:00:00 UTC
version 0.1
Tip revision: 31ec11b

\title{built-in plot functions for HLSM object}

	Functions to plot the likelihood and diagnostic-plot of posterior draws of the parameters from MCMC sample. 

	plotLikelihood(object,burnin = 0, thin = 1)


	\item{object}{object of class 'HLSM' obtained as an output from \code{HLSM()} or \code{HLSMfixedEF()}

	\item{burnin}{burnin value if want to plot burned chain}

	\item{thin}{a numeric thinning value}

	\item{chain}{a numeric vector of posterior draws of parameter of interest.}

 returns plot objects.

\author{Sam Adhikari}

#using advice seeking network of teachers in 15 schools
#to fit the data

#Random effect model#
priors = NULL
tune = NULL
initialVals = NULL
niter = 10 = HLSM(X = ps.edge.vars.mat,Y = ps.advice.mat,
	initialVals = initialVals,priors = priors,
	tune = tune,tuneIn = FALSE,dd = 2,niter = niter,
	intervention = 0)


intercept = getIntercept(
dim(intercept) ##is an array of dimension niter by 15

##look at the diagnostic plot of intercept for the first school

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