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, and 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 appendixes containing more advanced topics and/or difficult proofs. Moreover, there are three appendixes 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.
Выложил(а):Anatol