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2009-05-12

以下来自Amazon.com的介绍!

Introduction to the Mathematical and Statistical Foundations of Econometrics (Themes in Modern Econometrics) (Paperback)

by Herman J. Bierens (Author)
Key Phrases: maximum likelihood theory, lotto case, uniform weak law, Prove Theorem, Modes of Convergence, Mathematical Expectations

Editorial Reviews

Review
'The objective of this book is to use it as an introductory text for a Ph.D. level course in Econometrics. ... Appendixes are self contained with review which are easy to learn and understand. As a whole, I consider this book as unique and self-contained and it will be a great resource for researchers in the area of Econometrics.' Zentralblatt MATH

Product Description
This book is intended for use in a rigorous introductory Ph.D. 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.
 
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2009-5-12 01:10:00

简要目录如下:

1 Probability and Measure 1

Appendix1.A–Common Structure of the Proofs of Theorems 1.6 and 1.10 32
Appendix1.B–Extension of an Outer Measure to a Probability Measure
32

2 BorelMeasurability,Integration,andMathematical Expectations 37

Appendix2.A–Uniqueness of Characteristic Functions 61

3 Conditional Expectations 66

Appendix3.A–ProofofTheorem3.12 83

4 Distributions and Transformations 86

Appendix4.A–Tedious Derivations 104
Appendix4.B–Proof of Theorem4.4
106

5 The Multivariate Normal Distribution and Its Application to Statistical Inference 110

Appendix5.A–Proof of Theorem5.8 134

6 Modes of Convergence 137

Appendix6.A–Proof of the Uniform Weak Law of Large Numbers 164
Appendix6.B–Almost-Sure Convergence and Strong Laws of Large Numbers
167
Appendix6.C–Convergence of Characteristic Functions and Distributions
174

7 Dependent Laws of Large Numbers and Central Limit Theorems 179

Appendix7.A–Hilbert Spaces 199

8 Maximum Likelihood Theory 205

I ReviewofLinearAlgebra 229

II Miscellaneous Mathematics 283

III A Brief Review of ComplexAnalysis 298

IVTablesofCriticalValues 306

References 315
Index
317

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2009-5-12 01:11:00
学完本书,对高级计量帮助较大!
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2009-5-24 12:41:00

谢谢楼主分享啊,谢谢了

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2018-9-5 16:34:30
有答案的嘛
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