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Descrizione libro HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L1-9780198773122
Descrizione libro Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book offers an up-to-date coverage of the basic principles and tools of Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations, and the long available analytical results of Bayesian inference for linear regression models. About the SeriesAdvanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature. Codice articolo 9780198773122
Descrizione libro Hardcover. Condizione: new. Hardcover. This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers abroad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It containsalso an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods. This book covers the principles and tools of Bayesian inference in econometrics. Bayesian inference is a branch of statistics that integrates explicitly both data and prior information in model building, estimation and evaluation. The book shows how to use Bayesian methods in models suited to the analysis of macroeconomic and financial time series Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9780198773122
Descrizione libro Hardcover. Condizione: new. Hardcover. This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers abroad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It containsalso an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods. This book covers the principles and tools of Bayesian inference in econometrics. Bayesian inference is a branch of statistics that integrates explicitly both data and prior information in model building, estimation and evaluation. The book shows how to use Bayesian methods in models suited to the analysis of macroeconomic and financial time series This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780198773122