Parameter Estimation for Scientists and Engineers

Beschreibung

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.

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Adriaan van den Bos

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Electrical & Electronics Engineering Elektrotechnik u. Elektronik Experimental Design Numerical Methods & Algorithms Numerische Methoden u. Algorithmen Signal Processing Signalverarbeitung Statistics Statistik Versuchsplanung

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"An indispensable tool for scholars and research workers inmathematics and the mathematical sciences." (MathematicalReviews, 2009) "Despite its lean size, the book is able to cover many of thetechniques and theories in parameter estimation that are core toapplied sciences, and so this is certainly a valuable reference forresearchers and graduate students alike. The book's exposition islucid, making it an accessible reading for someone with areasonable background in elementary statistics. Thus I think anyonein applied sciences and engineering dealing with the implementationof expectation models and aiming to estimate model parameters willfind this book helpful. This is a great addition to resources inlearning or reviewing statistical tools that emphasize takingadvantage of valuable information from data and improving theprecision of estimation." (Technometrics, November 2008) "I highly recommend this book to practitioners who want tosystematically learn and use, new, better techniques for parameterestimation." (Computing Reviews, September 10, 2008) "...appropriate for students in advanced applied statisticscourses...even more useful as a supplemental resource..."(CHOICE, January 2008)
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