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Descripción Hardcover. Condición: 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. Nº de ref. del artículo: 9780198773122
Descripción Hardcover. Condición: 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. Nº de ref. del artículo: 9780198773122