Manual: document that typically Bayesian names are used even if ML is done
(@stepan removed trailing whitepaces)mr#1899
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@ -5401,6 +5401,16 @@ block decomposition of the model (see :opt:`block`).
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so that the sequence of proposals will be different across different runs.
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so that the sequence of proposals will be different across different runs.
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Finally, Dynare does not always properly distinguish between maximum
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likelihood and Bayesian estimation in its field names. While there is
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an important conceptual distinction between frequentist confidence intervals
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and Bayesian highest posterior density intervals (HPDI) as well as between
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posterior density and likelilhood, Dynare sometimes uses the Bayesian
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terms as a stand-in in its display of maximum likelihood results. An
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example is the storage of the output of the ``forecast``-option of
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``estimation`` with ML, which will use ``HPDinf/HPDsup`` to denote
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the confidence interval.
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*Algorithms*
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*Algorithms*
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The Monte Carlo Markov Chain (MCMC) diagnostics are generated by
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The Monte Carlo Markov Chain (MCMC) diagnostics are generated by
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@ -9617,7 +9627,7 @@ the :comm:`bvar_forecast` command.
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Variable set by the ``forecast`` command, or by the
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Variable set by the ``forecast`` command, or by the
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``estimation`` command if used with the ``forecast`` option
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``estimation`` command if used with the ``forecast`` option
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and if no Metropolis-Hastings has been computed (in that case,
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and ML or if no Metropolis-Hastings has been computed (in that case,
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the forecast is computed for the posterior mode). Fields are
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the forecast is computed for the posterior mode). Fields are
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of the form::
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of the form::
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@ -9629,38 +9639,34 @@ the :comm:`bvar_forecast` command.
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Lower bound of a 90% HPD interval [#f8]_ of forecast
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Lower bound of a 90% HPD interval [#f8]_ of forecast
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due to parameter uncertainty, but ignoring the effect
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due to parameter uncertainty, but ignoring the effect
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of measurement error on observed variables.
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of measurement error on observed variables. In case of ML,
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it stores the lower bound of the confidence interval.
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``HPDsup``
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``HPDsup``
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Upper bound of a 90% HPD forecast interval due to
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Upper bound of a 90% HPD forecast interval due to
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parameter uncertainty, but ignoring the effect of
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parameter uncertainty, but ignoring the effect of
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measurement error on observed variables.
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measurement error on observed variables. In case of ML,
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it stores the upper bound of the confidence interval.
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``HPDinf_ME``
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``HPDinf_ME``
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Lower bound of a 90% HPD interval [#f9]_ of forecast
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Lower bound of a 90% HPD interval [#f9]_ of forecast
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for observed variables due to parameter uncertainty
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for observed variables due to parameter uncertainty
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and measurement error.
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and measurement error. In case of ML,
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it stores the lower bound of the confidence interval.
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``HPDsup_ME``
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``HPDsup_ME``
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Upper bound of a 90% HPD interval of forecast for
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Upper bound of a 90% HPD interval of forecast for
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observed variables due to parameter uncertainty and
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observed variables due to parameter uncertainty and
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measurement error.
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measurement error. In case of ML,
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it stores the upper bound of the confidence interval.
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``Mean``
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``Mean``
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Mean of the posterior distribution of forecasts.
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Mean of the posterior distribution of forecasts.
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``Median``
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Median of the posterior distribution of forecasts.
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``Std``
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Standard deviation of the posterior distribution of forecasts.
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.. matvar:: oo_.PointForecast
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.. matvar:: oo_.PointForecast
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Set by the ``estimation`` command, if it is used with the
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Set by the ``estimation`` command, if it is used with the
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