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- Bayesian_vector_autoregression abstract "In statistics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR). In that respect, the difference with standard VAR models lies in the fact that the model parameters are treated as random variables, and prior probabilities are assigned to them.Vector autoregressions are flexible statistical models that typically include many free parameters. Given the limited length of standard macroeconomic datasets, Bayesian methods have become an increasingly popular way of dealing with this problem of over-parameterization. The general idea is to use informative priors to shrink the unrestricted model towards a parsimonious naïve benchmark, thereby reducing parameter uncertainty and improving forecast accuracy (see for a survey). A typical example is the shrinkage prior proposed by Robert Litterman, and subsequently developed by other researchers at University of Minnesota, which is known in the BVAR literature as the \"Minnesota prior\". The informativeness of the prior can be set by treating it as an additional parameter, based on a hierarchical interpretation of the model.Recent research has shown that Bayesian vector autoregression is an appropriate tool for modelling large data sets.".
- Bayesian_vector_autoregression wikiPageID "20484241".
- Bayesian_vector_autoregression wikiPageLength "3732".
- Bayesian_vector_autoregression wikiPageOutDegree "11".
- Bayesian_vector_autoregression wikiPageRevisionID "691520445".
- Bayesian_vector_autoregression wikiPageWikiLink Bayesian_econometrics.
- Bayesian_vector_autoregression wikiPageWikiLink Bayesian_inference.
- Bayesian_vector_autoregression wikiPageWikiLink Category:Bayesian_statistics.
- Bayesian_vector_autoregression wikiPageWikiLink Category:Econometrics.
- Bayesian_vector_autoregression wikiPageWikiLink Category:Multivariate_time_series_analysis.
- Bayesian_vector_autoregression wikiPageWikiLink Prior_probability.
- Bayesian_vector_autoregression wikiPageWikiLink Random_variable.
- Bayesian_vector_autoregression wikiPageWikiLink Robert_Litterman.
- Bayesian_vector_autoregression wikiPageWikiLink Statistics.
- Bayesian_vector_autoregression wikiPageWikiLink University_of_Minnesota.
- Bayesian_vector_autoregression wikiPageWikiLink Vector_autoregression.
- Bayesian_vector_autoregression wikiPageWikiLinkText "Bayesian vector autoregression".
- Bayesian_vector_autoregression wikiPageUsesTemplate Template:Econometrics-stub.
- Bayesian_vector_autoregression wikiPageUsesTemplate Template:Reflist.
- Bayesian_vector_autoregression subject Category:Bayesian_statistics.
- Bayesian_vector_autoregression subject Category:Econometrics.
- Bayesian_vector_autoregression subject Category:Multivariate_time_series_analysis.
- Bayesian_vector_autoregression type Econometric.
- Bayesian_vector_autoregression type Field.
- Bayesian_vector_autoregression type Redirect.
- Bayesian_vector_autoregression comment "In statistics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR). In that respect, the difference with standard VAR models lies in the fact that the model parameters are treated as random variables, and prior probabilities are assigned to them.Vector autoregressions are flexible statistical models that typically include many free parameters.".
- Bayesian_vector_autoregression label "Bayesian vector autoregression".
- Bayesian_vector_autoregression sameAs Q4874480.
- Bayesian_vector_autoregression sameAs m.04zvqsc.
- Bayesian_vector_autoregression sameAs Q4874480.
- Bayesian_vector_autoregression wasDerivedFrom Bayesian_vector_autoregression?oldid=691520445.
- Bayesian_vector_autoregression isPrimaryTopicOf Bayesian_vector_autoregression.