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Bayesian Econometrics

Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, mode...

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Bibliografski detalji
Daljnji autori:	Bernardi, Mauro (Urednik), Grassi, Stefano (Urednik), Ravazzolo, Francesco (Urednik)
Format:	Elektronički Poglavlje knjige
Jezik:	engleski
Izdano:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Teme:	Technology: general issues unconventional monetary policy transmission channel Bayesian TVP-SV-VAR Bayesian econometrics portfolio choice sentiments stock market predictability cryptocurrency Bitcoin forecasting point forecast density forecast dynamic model averaging dynamic model selection forgetting factors military and civilian spending DSGE model fiscal policy monetary policy Bayesian estimation Bayesian VAR density forecasting time-varying volatility ES CES function Bayesian nonlinear mixed-effects regression MCMC methods macroeconomic and financial applications
Online pristup:	DOAB: download the publication DOAB: description of the publication
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!

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Hybrid Advanced Techniques for Forecasting in Energy Sector
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Developments in Demographic Forecasting
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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
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Bayesian Methods for Statistical Analysis
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Efficient Reinforcement Learning using Gaussian Processes
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Fahrerabsichtserkennung und Risikobewertung für warnende Fahrerassistenzsysteme
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Evolution, Monitoring and Predicting Models of Rockburst Precursor Information for Rock Failure
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Evolution, Monitoring and Predicting Models of Rockburst Precursor Information for Rock Failure
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