Year

1988

Degree Name

Doctor of Philosophy

Department

Department of Mathematics

Abstract

Suppose that two populations, X and Y are available to an experimenter. Population X has probability density function (p.d.f.) f and population Y has p.d.f. h. It is assumed that of the populations has been replaced by another population with p.d.f. g. Let 𝐻1 denote the hypothesis that population Y has been replaced and let 𝐻2 denote the hypothesis that population X has been replaced. It is assumed that the experimenter can express a prior distribution which hypothesis is true.

The experimenter can take 𝑛 observations (𝑛 β‰₯ 1), and he must allocate these observations such that the amount of information about which hypothesis is true, using a given uncertainty function, is maximised. Sequential and non-sequential allocation of observations is considered for various uncertainty functions and different p.d.f.'s.

A generalisation of the problem is given for k+1 populations (π‘˜ β‰₯ 1). In particular, suppose that k+1 coins are available to the experimenter. It is known that one of these coins been replaced by a two-headed coin. Each toss of a coin has a certain cost. The experimenter can take observations until the two-headed coin is found. An optimal strategy that minimises expected cost of finding the two-headed coin is given.

Share

COinS
 

Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.