Isbn: 9780521542241 - introduction to the mathematical and statistical foundations of econometrics (17 risultati)

Condizione: acceptable. Book is considered to be in acceptable condition. The actual cover image may not match the stock photo. Book may have one or more of the following defects: noticeable wear on the cover dust jacket or spine; curved, dog eared or creased page s ; writing or highlighting inside or on the edges; sticker s or other adhesive on cover; CD DVD may not be included; and book may be a former library copy.…

Paperback. Condizione: New. This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained.…

TAPA BLANDA. Condizione: New.

Condizione: New. In English.

Condizione: New. pp. 344 Index.

paperback. Condizione: New. In shrink wrap. Looks like an interesting title.

Condizione: New. This book is intended for use in a rigorous introductory PhD level course in econometrics. Series Editor(s): Phillips, Peter C. B.; Ghysels, Eric; Smith, Richard J. Series: Themes in Modern Econometrics. Num Pages: 344 pages, 19 b/w illus. 12 tables. BIC Classification: KCH. Category: (P) Professional & Vocational. Dimension: 228 x 151 x 19. Weight in Grams: 524. . 2004. Paperback. . . . . Books ship from the US and Ireland. …

Condizione: New. This book is intended for use in a rigorous introductory PhD level course in econometrics. Series Editor(s): Phillips, Peter C. B.; Ghysels, Eric; Smith, Richard J. Series: Themes in Modern Econometrics. Num Pages: 344 pages, 19 b/w illus. 12 tables. BIC Classification: KCH. Category: (P) Professional & Vocational. Dimension: 228 x 151 x 19. Weight in Grams: 524. . 2004. Paperback. . . . . …

Paperback. Condizione: New. This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained.…

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained.…

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 344 | Sprache: Englisch | Produktart: Bücher | This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained. …

Softcover. Condizione: gut. 2011. Introduction to the Mathematical and Statistical Foundations of Econometrics In englischer Sprache. pages.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Condizione: New. Print on Demand pp. 344 Figures, 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 344 19 Diagrams.

Paperback. Condizione: new. Paperback. This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained. Intended for use in a rigorous introductory PhD level course in econometrics, or a field course in econometric theory, this book covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intended for use in a rigorous introductory PhD level course in econometrics, or a field course in econometric theory, this book covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to cl.…