| dc.contributor.author | Okungu, Jacob Oketch | |
| dc.contributor.author | Orwa, George Otieno | |
| dc.contributor.author | Otieno, Romanus Odhiambo | |
| dc.date.accessioned | 2023-02-16T13:28:04Z | |
| dc.date.available | 2023-02-16T13:28:04Z | |
| dc.date.issued | 2023-01 | |
| dc.identifier.issn | 2736-5484 | |
| dc.identifier.uri | DOI: http://dx.doi.org/10.24018/ejmath.2023.4.1.167 | |
| dc.identifier.uri | http://repository.must.ac.ke/handle/123456789/837 | |
| dc.description.abstract | 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 total based on Edgeworth expansion and Saddlepoint approximation. Three properties; unbiasedness,
efficiency, and coverage probability of the proposed estimators are compared. Based on the background of the two
techniques, we focus on confidence interval and coverage probabilities. Simulations on three theoretical data
variables in R revealed that Saddlepoint approximation performed better than Edgeworth expansion. Saddlepoint
approximation resulted into a smaller MSE, tighter confidence interval length, and higher coverage probability
compared to Edgeworth Expansion. The two techniques should be improved in estimation of parameters in other
sampling schemes like cluster sampling. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | EJ-MATH, European Journal of Mathematics and Statistics | en_US |
| dc.subject | Edgeworth expansion | en_US |
| dc.subject | Nonparametric estimator | en_US |
| dc.subject | Auxiliary variables Saddlepoint approximation. | en_US |
| dc.title | Comparing Edgeworth Expansion and Saddlepoint Approximation in Assessing the Asymptotic Normality Behavior of A Non-Parametric Estimator for Finite Population Total | en_US |
| dc.type | Article | en_US |
