fix typo
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941cda7655
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5058e4d00f
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@ -4216,10 +4216,10 @@ The Monte Carlo Markov Chain (MCMC) diagnostics are generated
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by the estimation command if @ref{mh_replic} is larger than 2000 and if
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option @ref{nodiagnostic} is not used. If @ref{mh_nblocks} is equal to one,
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the convergence diagnostics of @cite{Geweke (1992,1999)} is computed. It uses a
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chi square test to compare the means of the first and last draws specified in
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@ref{geweke_interval} (@pxref{geweke_interval}) after discarding the burnin of @ref{mh_drop}. The test is
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chi square test to compare the means of the first and last draws specified by
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@ref{geweke_interval} after discarding the burnin of @ref{mh_drop}. The test is
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computed using variance estimates under the assumption of no serial correlation
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as well as using tapering windows specified in @ref{taper_steps} (@pxref{taper_steps}).
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as well as using tapering windows specified in @ref{taper_steps}.
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If @ref{mh_nblocks} is larger than 1, the convergence diagnostics of
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@cite{Brooks and Gelman (1998)} are used instead.
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As described in section 3 of @cite{Brooks and Gelman (1998)} the univariate
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@ -4771,7 +4771,7 @@ Percent tapering used for the spectral window in the @cite{Geweke (1992,1999)}
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convergence diagnostics (requires @ref{mh_nblocks}=1). The tapering is used to
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take the serial correlation of the posterior draws into account. Default: @code{[4 8 15]}.
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@item geweke_interval = [@var{double} @var{double}]
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@item geweke_interval = [@var{DOUBLE} @var{DOUBLE}]
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@anchor{geweke_interval}
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Percentage of MCMC draws at the beginning and end of the MCMC chain taken
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to compute the @cite{Geweke (1992,1999)} convergence diagnostics (requires @ref{mh_nblocks}=1)
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