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Introduction to the Mathematical and...
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Bierens, Herman J.
Introduction to the Mathematical and Statistical Foundations of Econometrics.[electronic resource].
Record Type:
Language materials, printed : Monograph/item
[NT 15000414]:
330.015195
Title/Author:
Introduction to the Mathematical and Statistical Foundations of Econometrics.
Author:
Bierens, Herman J.
other author:
Gourieroux, Christian.
Published:
Cambridge : : Cambridge University Press,, 2004.
Description:
345 p.
Subject:
Econometrics.
ISBN:
9780511754012 (electronic bk.)
ISBN:
9780521834315 (print)
[NT 15000228]:
Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; 1 Probability and Measure; 2 Borel Measurability, Integration, and Mathematical Expectations; 3 Conditional Expectations; 4 Distributions and Transformations; 5 The Multivariate Normal Distribution and Its Application to Statistical Inference; 6 Modes of Convergence; 7 Dependent Laws of Large Numbers and Central Limit Theorems; 8 Maximum Likelihood Theory; Appendix I – Review of Linear Algebr; Appendix II – Miscellaneous Mathematics; Appendix III – A Brief Review of Complex Analysis; Appendix IV – Tables of Critical Values
[NT 15000229]:
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.
Online resource:
Click here to view book
Introduction to the Mathematical and Statistical Foundations of Econometrics.[electronic resource].
Bierens, Herman J.
Introduction to the Mathematical and Statistical Foundations of Econometrics.
[electronic resource]. - Cambridge :Cambridge University Press,2004. - 345 p.
Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; 1 Probability and Measure; 2 Borel Measurability, Integration, and Mathematical Expectations; 3 Conditional Expectations; 4 Distributions and Transformations; 5 The Multivariate Normal Distribution and Its Application to Statistical Inference; 6 Modes of Convergence; 7 Dependent Laws of Large Numbers and Central Limit Theorems; 8 Maximum Likelihood Theory; Appendix I – Review of Linear Algebr; Appendix II – Miscellaneous Mathematics; Appendix III – A Brief Review of Complex Analysis; Appendix IV – Tables of Critical Values
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.
Electronic reproduction.
Available via World Wide Web.
Mode of access: World Wide Web.
ISBN: 9780511754012 (electronic bk.)Subjects--Topical Terms:
186734
Econometrics.
Index Terms--Genre/Form:
336502
Electronic books.
LC Class. No.: HB139 .B527 2004eb
Dewey Class. No.: 330.015195
Introduction to the Mathematical and Statistical Foundations of Econometrics.[electronic resource].
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Introduction to the Mathematical and Statistical Foundations of Econometrics.
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[electronic resource].
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2004.
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345 p.
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Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; 1 Probability and Measure; 2 Borel Measurability, Integration, and Mathematical Expectations; 3 Conditional Expectations; 4 Distributions and Transformations; 5 The Multivariate Normal Distribution and Its Application to Statistical Inference; 6 Modes of Convergence; 7 Dependent Laws of Large Numbers and Central Limit Theorems; 8 Maximum Likelihood Theory; Appendix I – Review of Linear Algebr; Appendix II – Miscellaneous Mathematics; Appendix III – A Brief Review of Complex Analysis; Appendix IV – Tables of Critical Values
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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.
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Electronic reproduction.
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Available via World Wide Web.
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Gourieroux, Christian.
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Phillips, Peter C. B.
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Wickens, Michael.
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Click here to view book
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http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511754012
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