Abstract
One of the main problems in mathematical statistics is to find procedures which satisfy certain optimality conditions. A great variety of these conditions turns out to be equivalent to programming problems. Hence methods and results of the theory of linear and nonlinear programming can be applied to a set of statistical problems. The paper is a survey of such applications. Since there is always a timelag between the development of new methods in one field (programming) and their applications in another field (statistics), we are mainly concerned with applications of (infinite) linear programming. As another field of applications we discuss a problem in probability theory which is connected with the moment problem.
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