Madan Lal Puri – författare

Nonparametric techniques in statistics are those in which the data are ranked in order according to some particular characteristic. When applied to measurable characteristics, the use of such techniques often saves considerable calculation as compared with more formal methods, with only slight loss of accuracy. The field of nonparametric statistics is occupying an increasingly important role in statistical theory as well as in its applications. Nonparametric methods are mathematically elegant, and they also yield significantly improved performances in applications to agriculture, education, biometrics, medicine, communication, economics and industry.

Statistical Inference and Related Topics, Volume 2 presents the proceedings of the Summer Research Institute on Statistical Inference for Stochastic Processes, held in Bloomingdale, Indiana on July 31 to August 9, 1975. This book focuses on the theory of statistical inference for stochastic processes. Organized into 15 chapters, this volume begins with an overview of the case of continuous distributions with one real parameter. This text then reviews some results for multidimensional empirical processes and Brownian sheets when they are indexed by families of sets. Other chapters consider a class of cubic spline estimators of probability density functions over a finite interval. This book discusses as well the method to construct nonelimination type sequential procedures to select a subset containing all the superior populations. The final chapter deals with Markov sequences, which are among the most interesting available for study with a rich theory and varied applications. This book is a valuable resource for graduate students and research workers.

No detailed description available for "e;Nonparametric Methods in Statistics and Related Topics"e;.

No detailed description available for "e;Probability Theory and Extreme Value Theory"e;.