1. Introduction -- 2. Parametric models of observations -- 3. Distributions of observations -- 4. Precision and accuracy -- 5. Precise and accurate estimation -- 6. Numerical methods for parameter estimation -- 7. Solutions or partial solutions to problems -- Appendix A: Statistical results -- Appendix B: Vectors and matrices -- Appendix C: Positive semidefinite and positive definite matrices -- Appendix D: Vector and matrix differentiation
Summary
The subject of this book is estimating parameters of expectation models of statistical observations. The book describes the most important aspects of the subject for applied scientists and engineers. This group of users is often not aware of estimators other than least squares. Therefore one purpose of this book is to show that statistical parameter estimation has much more to offer than least squares estimation alone. In the approach of this book, knowledge of the distribution of the observations is involved in the choice of estimators. A further advantage of the chosen approach is that it un
Bibliography
Includes bibliographical references (pages 269-270) and index
Notes
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL
English
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