Browsing School of Pure and Applied Sciences by Author "Makumi, Nicholas"
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Bias Correction Technique for Estimating Quantiles of Finite Populations under Simple Random Sampling without Replacement
Makumi, Nicholas; Otieno, Romanus Odhiambo; Orwa, George O.; Were, Festus; Alexis, Habineza (Open Journal of Statistics, 2021-10)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 ... -
A bootstrap variance estimation under stratification with few units per stratum.
Habineza, Alexis; Otieno, Romanus Odhiambo; Orwa, George Otieno; Makumi, Nicholas (Journal of Statistics Applications & Probability Letters, 2022)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 ... -
Coverage properties of a neural network estimator of finite population total in high-dimensional space.
Were, Festus A.; Orwa, George Otieno; Otieno, Romanus Odhiambo; Makumi, Nicholas; Aldallal, Ramy (Journal of Mathematics, 2022)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 ... -
On quantiles estimation based on stratified sampling using multiplicative bias correction approach.
Makumi, Nicholas; Otieno, Romanus Odhiambo; Orwa, George Otieno; Habineza, Alexis (Journal of Mathematics, 2022)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 ...