Description Usage Arguments Value Author(s) Examples

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.

1 2 | ```
HLSMplotLikelihood(object, burnin = 0, thin = 1)
HLSMcovplots(fitted.model, burnin = 0, thin = 1)
``` |

`object` |
object of class 'HLSM' obtained as an output from |

`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 |

returns plot objects.

Sam Adhikari & Tracy Sweet

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
#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)
``` |

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