time-shift
Houtan Bastani 2013-09-23 14:31:43 +02:00
parent 941cda7655
commit 5058e4d00f
1 changed files with 4 additions and 4 deletions

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