ISBN 10: 0521542243 / ISBN 13: 9780521542241
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Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Part I. Probability and Measure: 1. The Texas lotto; 2. Quality control; 3. Why do we need sigma-algebras of events?; 4. Properties of algebras and sigma-algebras; 5. Properties of probability measures; 6. The uniform probability measures; 7. Lebesque measure and Lebesque integral; 8. Random variables and their distributions; 9. Density functions; 10. Conditional probability, Bayes's rule, and independence; 11. Exercises; A. Common structure of the proofs of Theorems 6 and 10; B. Extension of an outer measure to a probability measure; Part II. Borel Measurability, Integration and Mathematical Expectations: 12. Introduction; 13. Borel measurability; 14. Integral of Borel measurable functions with respect to a probability measure; 15. General measurability and integrals of random variables with respect to probability measures; 16. Mathematical expectation; 17. Some useful inequalities involving mathematical expectations; 18. Expectations of products of independent random variables; 19. Moment generating functions and characteristic functions; 20. Exercises; A. Uniqueness of characteristic functions; Part III. Conditional Expectations: 21. Introduction; 22. Properties of conditional expectations; 23. Conditional probability measures and conditional independence; 24. Conditioning on increasing sigma-algebras; 25. Conditional expectations as the best forecast schemes; 26. Exercises; A. Proof of theorem 22; Part IV. Distributions and Transformations: 27. Discrete distributions; 28. Transformations of discrete random vectors; 29. Transformations of absolutely continuous random variables; 30. Transformations of absolutely continuous random vectors; 31. The normal distribution; 32. Distributions related to the normal distribution; 33. The uniform distribution and its relation to the standard normal distribution; 34. The gamma distribution; 35. Exercises; A. Tedious derivations; B. Proof of theorem 29; Part V. The Multivariate Normal Distribution and its Application to Statistical Inference: 36. Expectation and variance of random vectors; 37. The multivariate normal distribution; 38. Conditional distributions of multivariate normal random variables; 39. Independence of linear and quadratic transformations of multivariate normal random variables; 40. Distribution of quadratic forms of multivariate normal random variables; 41. Applications to statistical inference under normality; 42. Applications to regression analysis; 43. Exercises; A. Proof of theorem 43; Part VI. Modes of Convergence: 44. Introduction; 45. Convergence in probability and the weak law of large numbers; 46. Almost sure convergence, and the strong law of large numbers; 47. The uniform law of large numbers and its applications; 48. Convergence in distribution; 49. Convergence of characteristic functions; 50. The central limit theorem; 51. Stochastic boundedness, tightness, and the Op and op-notations; 52. Asymptotic normality of M-estimators; 53. Hypotheses testing; 54. Exercises; A. Proof of the uniform weak law of large numbers; B. Almost sure convergence and strong laws of large numbers; C. Convergence of characteristic functions and distributions; Part VII. Dependent Laws of Large Numbers and Central Limit Theorems: 55. Stationary and the world decomposition; 56. Weak laws of large numbers for stationary processes; 57. Mixing conditions; 58. Uniform weak laws of large numbers; 59. Dependent central limit theorems; 60. Exercises; A. Hilbert spaces; Part VIII. Maximum Likelihood Theory; 61. Introduction; 62. Likelihood functions; 63. Examples; 64. Asymptotic properties if ML estimators; 65. Testing parameter restrictions; 66. Exercises. N° de ref. de la librería

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Sinopsis: The focus of this book is on clarifying the mathematical and statistical foundations of econometrics. Therefore, the text provides all the proofs, or at least motivations if proofs are too complicated, of the mathematical and statistical results necessary for understanding modern econometric theory. In this respect, it differs from other econometrics textbooks.

Book Description: This book is intended to be used in a first-semester Ph.D. level course in econometrics, but because it contains much advanced material, particularly in the appendices to the chapters, it is also suitable for a field course in econometric theory. The focus of this book is on understanding why rather than how the mathematical and statistical foundations of econometrics are established. Therefore, the text provides all the proofs, or at least motivations if proofs are too complicated, of the mathematical and statistical results necessary for understanding modern econometric theory. In this respect it differs from all other econometrics textbooks.

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Bierens, Herman J.
Editorial: Cambridge Univ. Press, USA (2004)
ISBN 10: 0521542243 ISBN 13: 9780521542241
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Descripción Cambridge Univ. Press, USA, 2004. Softcover. Estado de conservación: Fine. Size: Large 8vo (9 to 11 inches). ISBN: 0521542243. ISBN/EAN: 9780521542241. Nº de ref. de la librería 28639

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Bierens, Herman J.
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ISBN 10: 0521542243 ISBN 13: 9780521542241
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Descripción Cambridge University Press, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9780521542241_lsuk

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Bierens, Herman J.
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Descripción Cambridge University Press, 2004. PAP. Estado de conservación: New. New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería LQ-9780521542241

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Herman J. Bierens
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2004)
ISBN 10: 0521542243 ISBN 13: 9780521542241
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2004. Paperback. Estado de conservación: New. Language: English . Brand New Book ***** Print on Demand *****.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. Nº de ref. de la librería AAV9780521542241

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Herman J. Bierens
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2004. Paperback. Estado de conservación: New. Language: English . Brand New Book ***** Print on Demand *****. 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. Nº de ref. de la librería AAV9780521542241

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Descripción 2005. Paperback. Estado de conservación: NEW. 9780521542241 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE0462248

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Descripción Cambridge Univ Pr, 2005. Paperback. Estado de conservación: Brand New. 323 pages. 9.00x6.00x0.75 inches. In Stock. Nº de ref. de la librería __0521542243

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Bierens, Herman J.
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Descripción Cambridge University Press, Cambridge, 2004. Tapa blanda. Estado de conservación: New. Nº de ref. de la librería 100727329

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Descripción Cambridge University Press, 2004. PAP. Estado de conservación: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IQ-9780521542241

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Bierens, Herman J.
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Descripción Cambridge University Press, 2017. Paperback. Estado de conservación: New. Never used! This item is printed on demand. Nº de ref. de la librería 0521542243

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