This paper introduces a R-package for the stratification of a survey population using a
univariate stratification variable X and for the calculation of stratum sample sizes. Non …

In most economic and business surveys, the target variables (eg turnover of enterprises,
income of households, etc.) commonly resemble skewed distributions with many small and …

In the paper, we have discussed a modern approach to stratification of a finite population.
We have presented a general picture of univariate and multivariate stratification, and …

One of the main reasons for stratifying the population is to produce a gain in precision of the
estimates, in the sample surveys. For achieving this, one of the problem is determination of …

Using convenient stratification criteria such as geographical regions or other natural
conditions like age, gender, etc., is not beneficial in order to maximize the precision of the …

There is a need for better estimators of population size in places that have undergone rapid
growth and where collection of census data is difficult. We explored simulated estimates of …

The problem of finding an optimal sample stratification has been extensively studied in the
literature. In this paper, we propose a heuristic optimization method for solving the univariate …

This paper presents a general algorithm for constructing strata in a population using X, a
univariate stratification variable known for all the units in the population. Stratum h consists …

Sampling has evolved into a universally accepted approach for gathering information and
data mining as it is widely accepted that a reasonably modest-sized sample can sufficiently …

Survey statisticians use either approximate or optimisation‐based methods to stratify finite
populations. Examples of the former are the cumrootf (Dalenius & Hodges,) and geometric …