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Hardcover. Zustand: new. Hardcover. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread among scholars and researchers, and have become a staple part of undergraduate and postgraduate research programs. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject, as well as a comprehensive survey of the existing literature. The contributions include important new essays by many of the leading figures currently working in econometrics. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. This substantial international volume provides an overview of the applications and techniques at the cutting edge of the subject as well as providing a comprehensive survey of the existing literature. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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In den WarenkorbHardcover. Zustand: new. Hardcover. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread among scholars and researchers, and have become a staple part of undergraduate and postgraduate research programs. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject, as well as a comprehensive survey of the existing literature. The contributions include important new essays by many of the leading figures currently working in econometrics. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. This substantial international volume provides an overview of the applications and techniques at the cutting edge of the subject as well as providing a comprehensive survey of the existing literature. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbGebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. This substantial international volume provides an overview of the applications and techniques at the cutting edge of the subject as well as providing a comprehe.
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Hardcover. Zustand: new. Hardcover. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread among scholars and researchers, and have become a staple part of undergraduate and postgraduate research programs. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject, as well as a comprehensive survey of the existing literature. The contributions include important new essays by many of the leading figures currently working in econometrics. Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. This substantial international volume provides an overview of the applications and techniques at the cutting edge of the subject as well as providing a comprehensive survey of the existing literature. 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.
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Verlag: Cambridge University Press, 2004
ISBN 10: 0521591120 ISBN 13: 9780521591126
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Buch. Zustand: Neu. Simulation-Based Inference in Econometrics | Methods and Applications | Roberto Mariano (u. a.) | Buch | Gebunden | Englisch | 2004 | Cambridge University Press | EAN 9780521591126 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Sprache: Englisch
Verlag: Cambridge University Press, 2000
ISBN 10: 0521591120 ISBN 13: 9780521591126
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Zustand: New. PRINT ON DEMAND pp. 476.