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This Book Presents Modern Nonparametric Statistics from a Practical Point of View and Emphasises Methods in Regression and Curve Fitting.

DUBLIN, Ireland -- Research and Markets (http://www.researchandmarkets.com/reports/c71706) has announced the addition of "Nonparametric Statistics With Applications to Science and Engineering" to their offering.

This book presents modern nonparametric statistics from a practical point of view. It is primarily intended for use with engineers and scientists. While the book covers the necessary theorems and methods of rank tests in an applied fashion, the novelty lies in its emphasis on modern nonparametric methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical and nonparametric likelihood, and goodness of fit testing. MATLAB is the computing and programming system of choice throughout the book because of its special applicability for research analysis and simulation.

Author Info:

Paul H. Kvam, PhD, is Professor of Industrial and Systems Engineering at Georgia Institute of Technology. His research interests include nonparametric estimation, statistical reliability with applications to engineering, and analysis of complex and dependent systems. He has written over fifty refereed articles and was named a Fellow of the American Statistical Association in 2006.

Brani Vidakovic, PhD, is Professor of Statistics and Director of the Centre for Bioengineering Statistics at The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology. He has authored or co-authored three books and has published more than four dozen refereed articles. His areas of interest include wavelets, Bayesian inference, biostatistics, statistical methods in environmental research, and statistical education.

Contents:

Preface.

1. Introduction.

2. Probability Basics.

3. Statistics Basics.

4. Bayesian Statistics.

5. Order Statistics.

6. Goodness of Fit.

7. Rank Tests.

8. Designed Experiments.

9. Categorical Data.

10. Estimating Distribution Functions.

11. Density Estimation.

12. Beyond Linear Regression.

13. Curve Fitting Techniques.

14. Wavelets.

15. Bootstrap.

16. EM Algorithm.

17. Statistical Learning.

18. Nonparametric Bayes.

A. MATLAB.

B. WinBUGS.

MATLAB Index.

Author Index.

Subject Index.

For more information visit http://www.researchandmarkets.com/reports/c71706
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Publication:Business Wire
Date:Oct 16, 2007
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