Verlag: Cambridge University Press, 2004
ISBN 10: 0521542243 ISBN 13: 9780521542241
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Verlag: Cambridge University Press, 2004
ISBN 10: 0521542243 ISBN 13: 9780521542241
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Verlag: Cambridge University Press, 2004
ISBN 10: 0521542243 ISBN 13: 9780521542241
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Verlag: Cambridge University Press, 2004
ISBN 10: 0521834317 ISBN 13: 9780521834315
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In den Warenkorbhardcover. Zustand: Sehr gut. 344 Seiten; 9780521834315.2 Gewicht in Gramm: 1.
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ISBN 10: 0521834317 ISBN 13: 9780521834315
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Verlag: Cambridge University Press, 2011
ISBN 10: 0521542243 ISBN 13: 9780521542241
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Verlag: Cambridge University Press, 2004
ISBN 10: 0521542243 ISBN 13: 9780521542241
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In den WarenkorbTaschenbuch. Zustand: 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.
Verlag: Cambridge University Press, 2004
ISBN 10: 0521834317 ISBN 13: 9780521834315
Sprache: Englisch
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In den WarenkorbBuch. Zustand: 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.