Parameter Estimation for Scientists and Engineers
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A01=Adriaan van den Bos
aspects
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Author_Adriaan van den Bos
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Category=PBT
Category=PDE
Category=TBJ
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estimating
expectation
important
least squares
methodology
models
observations
parameter estimation
parameters
practical
precision
scientists
statistical
stepbystep
Product details
- ISBN 9780470147818
- Weight: 606g
- Dimensions: 165 x 240mm
- Publication Date: 07 Aug 2007
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Hardback
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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 unifies the underlying theory and reduces it to a relatively small collection of coherent, generally applicable principles and notions.
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.
