Description

Book Synopsis
Parameter Estimation for Scientists and Engineers discusses estimating parameters of expectation models of statistical observations. It aims to show scientists and engineers, who often are not aware of estimators other than least squares, that statistical parameter estimation has much more to offer than least squares estimation alone.

Trade Review
“An indispensable tool for scholars and research workers in mathematics and the mathematical sciences.” (Mathematical Reviews, 2009)

"Despite its lean size, the book is able to cover many of the techniques and theories in parameter estimation that are core to applied sciences, and so this is certainly a valuable reference for researchers and graduate students alike. The book's exposition is lucid, making it an accessible reading for someone with a reasonable background in elementary statistics. Thus I think anyone in applied sciences and engineering dealing with the implementation of expectation models and aiming to estimate model parameters will find this book helpful. This is a great addition to resources in learning or reviewing statistical tools that emphasize taking advantage of valuable information from data and improving the precision of estimation." (Technometrics, November 2008)

"I highly recommend this book to practitioners who want to systematically learn and use, new, better techniques for parameter estimation." (Computing Reviews, September 10, 2008)

"…appropriate for students in advanced applied statistics courses…even more useful as a supplemental resource…" (CHOICE, January 2008)



Table of Contents
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 Positive Definite Matrices.

Appendix D: Vector and Matrix Differentiation.

References.

Topic Index.

Parameter Estimation

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    RRP £116.95 – you save £11.69 (9%)

    Order before 4pm today for delivery by Fri 19 Jun 2026.

    A Hardback by Adriaan van den Bos


      View other formats and editions of Parameter Estimation by Adriaan van den Bos

      Publisher: John Wiley & Sons Inc
      Publication Date: 8/7/2007 12:00:00 AM
      ISBN13: 9780470147818, 978-0470147818
      ISBN10: 0470147814

      Description

      Book Synopsis
      Parameter Estimation for Scientists and Engineers discusses estimating parameters of expectation models of statistical observations. It aims to show scientists and engineers, who often are not aware of estimators other than least squares, that statistical parameter estimation has much more to offer than least squares estimation alone.

      Trade Review
      “An indispensable tool for scholars and research workers in mathematics and the mathematical sciences.” (Mathematical Reviews, 2009)

      "Despite its lean size, the book is able to cover many of the techniques and theories in parameter estimation that are core to applied sciences, and so this is certainly a valuable reference for researchers and graduate students alike. The book's exposition is lucid, making it an accessible reading for someone with a reasonable background in elementary statistics. Thus I think anyone in applied sciences and engineering dealing with the implementation of expectation models and aiming to estimate model parameters will find this book helpful. This is a great addition to resources in learning or reviewing statistical tools that emphasize taking advantage of valuable information from data and improving the precision of estimation." (Technometrics, November 2008)

      "I highly recommend this book to practitioners who want to systematically learn and use, new, better techniques for parameter estimation." (Computing Reviews, September 10, 2008)

      "…appropriate for students in advanced applied statistics courses…even more useful as a supplemental resource…" (CHOICE, January 2008)



      Table of Contents
      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 Positive Definite Matrices.

      Appendix D: Vector and Matrix Differentiation.

      References.

      Topic Index.

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