Bayesian Inference Dynamic Econometric by Bauwens Luc (43 results)

Trade paperback. Trade paperback (US). Glued binding. 366 p. Advanced Texts in Econometrics. Audience: General/trade. Very good. light shelfwear, previous owner name on first page.

Paperback. Condition: Good. This book is in good condition; no remainder marks. It does have some cover shelfwear, edge wear, corner wear. Inside pages have no writing. ; Advanced Texts In Econometrics; 23.4 X 15.6 X 1.94 centimeters; 366 pages.

Condition: New. pp. 368.

Condition: New. pp. 368 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:0198773137.

Condition: New.

Condition: New. 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. Series: Advanced Texts in Econometrics. Num Pages: 366 pages, graphs. BIC Classification: KCH; PBT; PBWH; UGK. Category: (P) Professional & Vocational. Dimension: 234 x 157 x 21. Weight in Grams: 514. . 2000. Paperback. . . . . …

Condition: As New. Unread book in perfect condition.

Condition: New. 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. Series: Advanced Texts in Econometrics. Num Pages: 366 pages, graphs. BIC Classification: KCH; PBT; PBWH; UGK. Category: (P) Professional & Vocational. Dimension: 234 x 157 x 21. Weight in Grams: 514. . 2000. Paperback. . . . . Books ship from the US and Ireland. …

Condition: New.

Condition: New. In English.

Paperback. Condition: New. 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 a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.…

Condition: As New. Unread book in perfect condition.

Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Condition: New. 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 a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.…

Broschiert. Condition: Gut. 350 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 545. …

Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: New. 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. Series: Advanced Texts in Econometrics. Num Pages: 366 pages, graphs. BIC Classification: KCH; PBT; PBWH; UGK. Category: (P) Professional & Vocational. Dimension: 242 x 163 x 24. Weight in Grams: 673. . 2000. Hardback. . . . . …

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New. 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. Series: Advanced Texts in Econometrics. Num Pages: 366 pages, graphs. BIC Classification: KCH; PBT; PBWH; UGK. Category: (P) Professional & Vocational. Dimension: 242 x 163 x 24. Weight in Grams: 673. . 2000. Hardback. . . . . Books ship from the US and Ireland. …

Condition: New. In English.

Condition: gut. 1999. Bayesian Inference in Dynamic Econometric Models. Advanced Texts in Econometrics. In englischer Sprache. pages.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Condition: 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.…

Paperback. Condition: 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability.…