An improved method for finite population total estimation is proposed using a multiplicative semi-parametric bias reduction density function. The density is first applied to estimate a non-parametric regression model which ...

The measurement errors exist and sample survey results are always uncertain because only a portion of the population is measured. Larger samples and superior measurement tools can help to reduce this uncertainty. The ...

The problem in nonparametric estimation of finite population total particularly when dealing with high-dimensional datasets is addressed in this paper. The coverage properties of a robust finite population total estimator ...

In the context of stratified sampling, we develop a nonparametric regression technique to estimating finite population quantiles in model-based frameworks using a multiplicative bias correction strategy. Furthermore, the ...

Abstract — Sample surveys concern themselves with drawing inferences about the population based on sample statistics. We assess the asymptotic normality behavior of a proposed nonparametric estimator for finite a population ...

Statelessness is the absence of any Nationality. These include the Pemba, Shona, Galjeel, people of Burundi and Rwanda descent, and children born in Kenya to British Overseas Citizens after 1983. Frequently, they are not ...

In this paper, the problem of nonparametric estimation of finite population quantile function using multiplicative bias correction technique is considered. A robust estimator of the finite population quantile function based ...

The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric kernel discriminant ...