Reddy, Karuna G. and Khan, Mohammad G.M. (2017) Optimal Stratification of Univariate Populations via stratify R Package. [Conference Proceedings]
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Abstract
Stratification reduces the variance of sample estimates for population parameters by creating homogeneous
strata. Often, surveyors stratify the population using the most convenient variables such
as age, sex, region, etc. Such convenient methods often do not produce internally homogeneous
strata, hence, the precision of the estimates of the variables of interest could be further improved.
This paper introduces an R-package called ’stratifyR’ whereby it proposes a method for optimal
stratification of survey populations for a univariate study variable that follows a particular distribution
estimated from a data set that is available to the surveyor. The stratification problem is
formulated as a mathematical programming problem and solved by using a dynamic programming
technique. Methods for several distributions such as uniform, weibull, gamma, normal, lognormal,
exponential, right-triangular, cauchy and pareto are presented. The package is able to construct
optimal stratification boundaries (OSB) and calculate optimal sample sizes (OSS) under Neyman
allocation. Several examples, using simulated data, are presented to illustrate the stratified designs
that can be constructed with the proposed methodology. Results reveal that the proposed method
computes OSB that are precise and comparable to the established methods. All the calculations
presented in this paper were carried out using the stratifyR package that will be made available on
CRAN.
| Item Type: | Conference Proceedings |
|---|---|
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Office of the PVC (R&I) Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences |
| Depositing User: | Karuna Reddy |
| Date Deposited: | 13 Mar 2017 02:03 |
| Last Modified: | 15 Mar 2017 03:46 |
| URI: | https://repository.usp.ac.fj/id/eprint/9617 |
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