summary.Rd 1.88 KB
 Gilles Kratzer committed Feb 28, 2019 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 % summary.mcmcabn.Rd --- % Author : Gilles Kratzer % Created on : 28.02.2019 % Last modification : %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{summary.mcmcabn} \alias{summary.mcmcabn} \title{Function to summarize MCMC run generated by mcmcabn} \usage{ \method{summary}{mcmcabn}(object, quantiles = c(0.025, 0.25, 0.5, 0.75, 0.975), lag.max = 10, \dots) } \arguments{ \item{object}{object of class \code{mcmcabn}.} \item{quantiles}{numeric vector of probabilities with values in [0,1]. (Values up to 2e-14 outside that range are accepted and moved to the nearby endpoint.)}  Gilles Kratzer committed Mar 01, 2019 21  \item{lag.max}{maximum lag at which to calculate the \link{acf}. Default is set to 10.}  Gilles Kratzer committed Feb 28, 2019 22 23 24  \item{\dots}{arguments to be passed to methods.} }  Gilles Kratzer committed Mar 01, 2019 25 \description{Summary method for mcmcabn objects.}  Gilles Kratzer committed Feb 28, 2019 26   Gilles Kratzer committed Mar 01, 2019 27 \details{The summary function for \code{mcmcabn} objects returns multiple summary metrics for assesing the quality of the MCMC run. Thinning is the number of thinned MCMC steps for one MCMC returned.}  Gilles Kratzer committed Feb 28, 2019 28   Gilles Kratzer committed Mar 01, 2019 29 \value{This method prints: the number of burn-in steps, the number of MCMC steps, the thinning, the maximum achieved score, the empirical mean of the MCMC samples, the empirical standard deviation of the MCMC samples, the user defined quantiles of the posterior network score, the global acceptance rate, a table of the accepted and rejected moves in function of the methods used, the sample size adjusted for autocorrelation and the autocorrelations by lag.}  Gilles Kratzer committed Feb 28, 2019 30 31 32 33 34 35 36 37 38  \author{Gilles Kratzer} \references{ Scutari, M. (2010). Learning Bayesian Networks with the bnlearn R Package. Journal of Statistical Software, 35(3), 1 - 22. doi:http://dx.doi.org/10.18637/jss.v035.i03. } \examples{  Reinhard Furrer committed Oct 29, 2019 39 40 ## Example from the asia dataset from Lauritzen and Spiegelhalter (1988) ## provided by Scutari (2010)  Gilles Kratzer committed Feb 28, 2019 41 42 #summary the MCMC run summary(mcmc.out.asia)  Gilles Kratzer committed Mar 07, 2019 43 }