Parameter Estimation for Scientists and Engineers

Step–by–Step Methodology for Practical Parameter Estimation
Written for applied scientists and engineers, this book covers the most important aspects of estimating parameters of expectation models of statistical observations. The author demonstrates that statistical parameter estimation has much more to offer than least squares estimation alone, and explains how a priori knowledge may be used more fully to improve the precision of estimating. Parameter Estimation for Scientists and Engineers presents:
An explanation of statistical parametric models of observations, and why they are used
A description of distributions of observations including exponential families of distributions
Fisher information and the Cramér–Rao lower bound, and how they are used to judge the quality of parameter estimators and experimental designs
The maximum likelihood method and the least squares method for estimating parameters of expectation models
A discussion of model hypothesis testing
Numerical methods suitable for the parameter estimation problems dealt with in this book, as well as an exploration of how to use these methods in practice
Complete with sixty–two examples, eighty–nine problems and solutions, and thirty–four figures, Parameter Estimation for Scientists and Engineers is an invaluable reference for professionals and an ideal text for advanced undergraduate and graduate–level students in all disciplines of engineering and applied science.

Spis treści:
Preface.
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 Po sitive Definite Matrices.
Appendix D: Vector and Matrix Differentiation.
References.
Topic Index.

Nota biograficzna:
Adriaan van den Bos, PhD, is Professor Emeritus of the Department of Applied Physics of Delft University of Technology, The Netherlands. He carries out research in the field of statistical signal processing, parameter estimation, statistics, and application of parameter estimation to problems in applied physics, to optics and electron–optics in particular. He authored or coauthored some fifty journal papers, and his paper "Alternative Interpretation of Maximum Entropy Spectral Analysis," published in IEEE Transactions on Information Theory in 1971, became an official Citation Classic. In addition to journal papers, he has contributed to a number of books. In 2000, Dr. van den Bos was elected to the grade of Fellow of the Institute of Electrical and Electronics Engineers for his fundamental work in modeling and identification and its application in instrumentation and signal processing.

Okładka tylna:
Step–by–Step Methodology for Practical Parameter Estimation
Written for applied scientists and engineers, this book covers the most important aspects of estimating parameters of expectation models of statistical observations. The author demonstrates that statistical parameter estimation has much more to offer than least squares estimation alone, and explains how a priori knowledge may be used more fully to improve the precision of estimating. Parameter Estimation for Scientists and Engineers presents:
An explanation of statistical parametric models of observations, and why they are used
A description of distributions of observations including exponential families of distributions
Fisher information and the Cramér–Rao lower bound, and how they are used to judge the quality of parameter estimators and experimental designs
The maximum likelihood method and the least squares method for estimating parameters of expectation models
A discussion of model hypothesis testing
Numerical methods suitable for the parameter estimation problems dealt with in this book, as well as an exploration of how to use these methods in practice
Complete with sixty–two examples, eighty–nine problems and solutions, and thirty–four figures, Parameter Estimation for Scientists and Engineers is an invaluable reference for professionals and an ideal text for advanced undergraduate and graduate–level students in all disciplines of engineering and applied science.