Mathematical Programming in Statistics

Since its original publication in 1981, mathematical programming has grown in popularity, yet this treatise remains one of the most comprehensive treatments of the subject available. It covers linear regression analysis, linear statistical models, sampling, cluster analysis and testing theories. 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.