A MATHEMATICAL PROGRAMMING APPROACH IN OPTIMUM STRATIFICATION UNDER NEYMAN ALLOCATION FOR TWO STRATIFYING VARIABLES

The current study discusses the solution for obtaining stratification points under Neyman allocation having one study variable and two auxiliary variables. Using dynamic programming approach non-linear programming problem has been solved. The proposed technique has gained in precision rather than using only one auxiliary variable. Numerical illustration has been given in which each of the auxiliary variable is supposed to follow different distribution. Through the empirical study, the proposed method has been compared with the Ravindra and Sukhatme (1969) and Khan et al.(2005) methods with the conclusion of having its more relative efficiency.

A Dexterous Optional Randomized Response Model

This article addresses the problem of estimating the proportion π S of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is more efficient than Kim and Warde stratified randomized response model and Mangat model.