Nonparametric Statistics

Theory and Methods

The number of books on Nonparametric Methodology is quite small as compared to, say, on Design of Experiments, Regression Analysis, Multivariate Analysis, etc.

Because of being perceived as less effective, nonparametric methods are still the second choice. Actually, it has been demonstrated time and again that they are useful. We feel that there is still need for proper texts/applications/reference books on Nonparametric Methodology.

This book will introduce various types of data encountered in practice and suggest the appropriate nonparametric methods, discuss their properties through null and non-null distributions whenever possible and demonstrate the very minor loss in power and efficiency in the nonparametric method, if any.

The book will cover almost all topics of current interest such as bootstrapping, ranked set sampling, techniques for censored data and Bayesian analysis under nonparametric set ups.

Contents:

• Principles of Statistical Inference
• Order Statistics
• Empirical Distribution Function
• The Goodness of Fit Problem
• The One Sample Problem
• Optimal Nonparametric Tests
• The Two Sample Problem
• The Several Sample Problem
• Tests for Independence
• Nonparametric Density Estimation
• Regression Analysis
• Nonparametric Bayesian Methods
• Appendix

Readership: Graduate and senior undergraduate students of statistics.