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Descrizione libro TAPA BLANDA. Condizione: New. Codice articolo 100459486
Descrizione libro Condizione: New. Codice articolo 80384-n
Descrizione libro PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9780198773139
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Descrizione libro Condizione: New. Codice articolo 80384-n
Descrizione libro Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Codice articolo C9780198773139
Descrizione libro Paperback. Condizione: new. Paperback. 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 work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. Several examples illustrate the methods. 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 9780198773139
Descrizione libro PAP. 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 L0-9780198773139
Descrizione libro Paperback. Condizione: new. Paperback. 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 work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. Several examples illustrate the methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9780198773139