USP Electronic Research Repository

Optimum stratification for exponential study variable under Neyman allocation

Khan, Mohammad G.M. and Sehar, N. and Ahsan, M.J. (2005) Optimum stratification for exponential study variable under Neyman allocation. Journal of the Indian Society of Agricultural Statistics, 59 (2). pp. 146-150. ISSN 0019-6363

[img] PDF - Published Version
Restricted to Repository staff only

Download (333Kb)

    Abstract

    For stratified sampling to be efficient the strata should be as homogeneous as possible with respect to the main study variable. In other words, the stratum boundaries are so chosen that the stratum variances are as small as possible. This could be done effectively when the frequency distribution ofthe main study variable is known. Usually this frequency distribution is unknown but it is possible to approximate it from the past experience and prior knowledge about the population. In the present paper the problem ofoptimum stratification is studied and formulated as a Mathematical Programming Problem (MPP) assuming exponential frequency distribution of the main study variable. The stratum boundaries are optimum in the sense that they minimize'the sampling variance ofthe stratified sample mean under Neyman allocation. The formulated MPP is separable with respect to the decision variables and is treated as a multistage decision problem. A solution procedure is developed using dynamic programming technique. A numerical example is also given to show the computational efficiency of the procedure.

    Item Type: Journal Article
    Subjects: Q Science > QA Mathematics
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
    Depositing User: Ms Mereoni Camailakeba
    Date Deposited: 20 Apr 2005 16:05
    Last Modified: 16 Mar 2017 10:10
    URI: http://repository.usp.ac.fj/id/eprint/3373
    UNSPECIFIED

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...