Commit a08c6a62 authored by Gilles Kratzer's avatar Gilles Kratzer
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typos

parent b7f00e94
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......@@ -2,8 +2,8 @@
\docType{data}
\alias{dist.asia}
\title{Named list of distribution to analyze asia dataset}
\description{Named list of distribution to analyze asia dataset
\title{Named list of distributions to analyze asia dataset}
\description{Named list of distribution to analyze asia dataset.
}
\usage{data("mcmc_run_asia")}
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......@@ -3,7 +3,7 @@
\alias{mcmc_run_asia}
\title{MCMC search from the synthetic asia dataset for use with mcmcabn library examples}
\description{10^5 MCMC runs with 1000 burn in run from the asia synthetic datasets from Lauritzen and Spiegelhalter (1988) provided by Scutari (2010).
\description{10^5 MCMC runs with 1000 burn-in runs from the asia synthetic dataset from Lauritzen and Spiegelhalter (1988) provided by Scutari (2010).
}
\usage{data("mcmc_run_asia")}
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......@@ -32,7 +32,7 @@ terms, `.` replaces all the variables in name. Additional, when one want to excl
If the formula argument is not provided the function returns the average support of all individual arcs using a named matrix.
}
\value{A probability}
\value{A frequency for the requested query. Alternatively a matrix with arc-wise frequencies.}
\author{Gilles Kratzer}
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......@@ -18,16 +18,15 @@
\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.)}
\item{lag.max}{maximum lag at which to calculate the acf. Default is set to 10.}
\item{lag.max}{maximum lag at which to calculate the \link{acf}. Default is set to 10.}
\item{\dots}{arguments to be passed to methods.}
}
\description{Summary method for mcmcabn objects.
}
\description{Summary method for mcmcabn objects.}
\details{The summary function for mcmcabn objects returns multiple summary metrics for assesing the quality of the MCMC run.}
\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.}
\value{This method print: 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.}
\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.}
\author{Gilles Kratzer}
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