Arbeitspapier
Analysis of variance for bayesian inference
This paper develops a multi-way analysis of variance for non-Gaussian multivariate distributions and provides a practical simulation algorithm to estimate the corresponding components of variance. It specifically addresses variance in Bayesian predictive distributions, showing that it may be decomposed into the sum of extrinsic variance, arising from posterior uncertainty about parameters, and intrinsic variance, which would exist even if parameters were known. Depending on the application at hand, further decomposition of extrinsic or intrinsic variance (or both) may be useful. The paper shows how to produce simulation-consistent estimates of all of these components, and the method demands little additional effort or computing time beyond that already invested in the posterior simulator. It illustrates the methods using a dynamic stochastic general equilibrium model of the US economy, both before and during the global financial crisis.
- Sprache
-
Englisch
- Erschienen in
-
Series: ECB Working Paper ; No. 1409
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Forecasting Models; Simulation Methods
- Thema
-
Analysis of variance
Bayesian inference
posterior simulation
predictive distributions
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Geweke, John
Amisano, Gianni
- Ereignis
-
Veröffentlichung
- (wer)
-
European Central Bank (ECB)
- (wo)
-
Frankfurt a. M.
- (wann)
-
2011
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Geweke, John
- Amisano, Gianni
- European Central Bank (ECB)
Entstanden
- 2011
Ähnliche Objekte (12)
Inference in Bayesian proxy-SVARs
Robust Bayesian inference in proxy SVARs
Bayesian inference for the tangent portfolio
Robust Bayesian inference in proxy SVARs
Ensemble MCMC sampling for robust Bayesian inference
Robust Bayesian inference for set-identified models
Emotions, Bayesian inference, and financial decision making
Robust Bayesian inference for set-identified models
Linear statistical inference for global and local minimum variance portfolios
Bayesian inference for the mixed-frequency VAR model
BayesMultiMode: Bayesian Mode Inference in R
A Bayesian approach for inference on probabilistic surveys
Inference in Bayesian proxy-SVARs
Robust Bayesian inference in proxy SVARs
Bayesian inference for the tangent portfolio
Robust Bayesian inference in proxy SVARs
Ensemble MCMC sampling for robust Bayesian inference
Robust Bayesian inference for set-identified models
Emotions, Bayesian inference, and financial decision making
Robust Bayesian inference for set-identified models
Linear statistical inference for global and local minimum variance portfolios
Bayesian inference for the mixed-frequency VAR model
BayesMultiMode: Bayesian Mode Inference in R
A Bayesian approach for inference on probabilistic surveys
Inference in Bayesian proxy-SVARs
Robust Bayesian inference in proxy SVARs
Bayesian inference for the tangent portfolio
Robust Bayesian inference in proxy SVARs
Ensemble MCMC sampling for robust Bayesian inference
Robust Bayesian inference for set-identified models
Emotions, Bayesian inference, and financial decision making
Robust Bayesian inference for set-identified models
Linear statistical inference for global and local minimum variance portfolios
Bayesian inference for the mixed-frequency VAR model
BayesMultiMode: Bayesian Mode Inference in R