Search

This study investigates the process for estimating the mean number of individuals having rare sensitive attribute in stratified random sampling as well as in stratified random double sampling using Poisson distribution. The properties of the suggested estimation procedures are deeply examined. Empirical studies are performed to support the theoretical results, which show the dominance of the proposed estimators over well-known existing estimators. The results are interpreted and suitable recommendations have been put forward to the survey practitioners. [ABSTRACT FROM AUTHOR]

This work presents a randomization device for the estimation of population mean related to quantitative sensitive characteristics using blank card strategy. Measure of privacy protection for the proposed randomized response models have been described. The proposed technique provides the unbiased estimation procedures of population mean along with enhanced privacy protection of the respondents. Empirical studies are performed to support the theoretical results and efficiency of the models are also verified by suggesting an unified measure which show the dominance of the proposed models over existing models. Results are analyzed and suitable recommendations are put forward to the survey practitioners. [ABSTRACT FROM AUTHOR]

The present study deals with the estimation procedures of the mean number of persons bearing a rare sensitive attribute in the clustered population under two-stage sampling scheme. The resultant estimators have been suggested using two-stage randomized response model when a rare unrelated attribute is assumed to be known as well as unknown. The properties of resultant estimators are studied where the first-stage samples are drawn using the probability proportional to the size with replacement sampling scheme. The estimation procedures have been further extended for the stratified clustered population. The empirical studies are performed for the validation of the suggested estimation procedures. Recommendations have been made to survey practitioners for their real-life applications. [ABSTRACT FROM AUTHOR]

Bioconvection is a fascinating phenomenon observed in various biological systems, where the motion of motile microorganisms generates fluid flow patterns. This article explores the occurrence and characteristics of bioconvection within the context of a jet flow. The study of bioconvection in jet flow involves the interaction between motile microorganisms and the fluid dynamics of the surrounding medium. Microorganisms such as bacteria and algae are known to exhibit directed swimming behavior, which can lead to the formation of dynamic flow structures. Investigating the mechanisms underlying bioconvection in jet flow requires a multidisciplinary approach encompassing fluid dynamics, microbial ecology, and mathematical modeling. Experimental techniques, such as microscopy and particle image velocimetry, along with computational simulations, are employed to analyze the complex interactions between microorganisms and the fluid flow. In this regard, a supportive mathematical model is designed using partial differential equations (PDEs) which are later transformed into ordinary differential equations using similarity transformations. The resulting system of equations is solved using the RKF-45 method and the outcomes are recorded in tables and graphs. The consideration of thermophoresis has shown a significant impact on the heat and mass transfer of the jet flow and both these profiles are observed to increase with thermophoresis. Meanwhile, the Schmidt number decrease their respective mass profiles. Furthermore, the porosity is found to create a drag force which tends to oppose the fluid flow. [ABSTRACT FROM AUTHOR]

In this paper, an efficient generalized estimation strategy has been proposed to present the problem of estimation of current population mean Y ¯ of study variable y in two-occasion rotation sampling. The properties of the proposed estimation procedure have been deeply examined and its optimum replacement strategy is formulated. Empirical studies are carried out to show the superiority of the proposed estimator over the sample mean estimator, natural successive sampling estimator (when no auxiliary information is used) and some well-known recent contemporary estimators under various situations. Numerical results are given in support of the study and recommendations are also made to the survey practitioners. [ABSTRACT FROM AUTHOR]

The present study confirms the influential role of a positively and a negatively correlated auxiliary variables in enhancing the precision of estimates of current population mean in two occasion rotation (successive) sampling. Exponential-type estimators of current population mean have been proposed for three different situations: (i) the information on a positively correlated auxiliary variable is readily available on both occasions (ii) the information on a negatively correlated auxiliary variable is readily available on both occasions and (iii) the information on both positively and negatively correlated auxiliary variables are readily available on both the occasions. The characteristics of the proposed estimators have been explored and their efficacious performances are compared with the natural and recent contemporary estimators. Optimum replacement strategies of the proposed estimation procedures have been formulated. Simulation and empirical studies are carried out to justify the proposition of the proposed estimators and appropriate recommendations have been put forward to the survey practitioners. [ABSTRACT FROM AUTHOR]

Unbiased estimation procedures of the mean total number of persons with a rare sensitive attribute apply for a clustered population under two-stage and stratified two-stage sampling schemes. Randomized response model is used to obtain the estimators, when the parameter of an unrelated rare non-sensitive attribute is either known or unknown. The variances of the resultant estimators are derived and their unbiased estimates are expressed. Numerical comparisons show that dispersions in the estimates are lower than other contemporary estimators. [ABSTRACT FROM AUTHOR]