Asymptotic Theory of Nonlinear Regression (Hardcover, 1997 ed.)

This book presents up-to-date mathematical results in asymptotic theory on nonlinear regression on the basis of various asymptotic expansions of least squares, its characteristics, and its distribution functions of functionals of Least Squares Estimator. It is divided into four chapters. In Chapter 1 assertions on the probability of large deviation of normal Least Squares Estimator of regression function parameters are made. Chapter 2 indicates conditions for Least Moduli Estimator asymptotic normality. An asymptotic expansion of Least Squares Estimator as well as its distribution function are obtained and two initial terms of these asymptotic expansions are calculated. Separately, the Berry-Esseen inequality for Least Squares Estimator distribution is deduced. In the third chapter asymptotic expansions related to functionals of Least Squares Estimator are dealt with. Lastly, Chapter 4 offers a comparison of the powers of statistical tests based on Least Squares Estimators. The Appendix gives an overview of subsidiary facts and a list of principal notations. Additional background information, grouped per chapter, is presented in the Commentary section. The volume concludes with an extensive Bibliography. Audience: This book will be of interest to mathematicians and statisticians whose work involves stochastic analysis, probability theory, mathematics of engineering, mathematical modelling, systems theory or cybernetics.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	Mathematics and Its Applications, 389
Release date:	2001
First published:	1997
Authors:	A. A. Ivanov
Dimensions:	235 x 155 x 20mm (L x W x T)
Format:	Hardcover
Pages:	330
Edition:	1997 ed.
ISBN-13:	978-0-7923-4335-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics
LSN:	0-7923-4335-2
Barcode:	9780792343356

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