Mathematical Programming in Statistics

Develops the theory and methods of mathematical programming for application to problems in statistics. Exploits the structure of the problem under consideration in order to develop efficient solutions. Provides extensive examples of applications, tables on minimal connected designs, BIB design with k-3, bibliographic notes and references. Prologue.

Linear Regression Analysis.

Generalized Inverses in Linear Statistical Models.

Theory of Testing Statistical Hypotheses.

Sampling.

Design and Analysis of Experiment.

Cluster Analysis.

Epilogue.

Index.

T. S. Arthanari and Dr. Yadolah Dodge are the authors of Mathematical Programming in Statistics, published by Wiley.