Estimating a Finite Population Total using a Density Function

Estimating a Finite Population Total using a Density Function

  • Dioggban Jakperik CK Tedam University of Technology and Applied Sciences
  • Romanus Otieno Odhiambo Meru University of Science and Technology
  • Jacob Oketch Okungu Meru University of Science and Technology

Abstract

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 describes the relationship between the study variable and the auxiliary variable. For each value of the study variable, there exist a corresponding value of the auxiliary variable in the population. The proposed estimator is compared to the expansion estimator and the NadarayaWatson estimator using bandwidths (h = 0.25, 0.5, 0.75) respectively through a simulation study on the Ghana Living Standards Survey Round Six data. The proposed estimator performed better than its competitors yielding the lowest Root Average Squared Error (ARE). The estimator can be applied to datasets with high variances without transformation. Its optimum efficiency and precision are achieved when the sample size is large. 

Published
2021-05-02
How to Cite
JAKPERIK, Dioggban; ODHIAMBO, Romanus Otieno; OKUNGU, Jacob Oketch. Estimating a Finite Population Total using a Density Function. Eurasian Bulletin of Mathematics (ISSN: 2687-5632), [S.l.], v. 4, n. 1, p. 32-37, may 2021. ISSN 2687-5632. Available at: <http://www.ebmmath.com/index.php/EBM/article/view/68>. Date accessed: 19 june 2021.