Estimation of the Parameters of the New Weibull-Pareto Distribution Using Ranked Set Sampling

Samuh, Monjed H.; Al-Omari, Amer I.; Koyuncu, Nursel

dc.contributor.author	Samuh, Monjed H.
dc.contributor.author	Al-Omari, Amer I.
dc.contributor.author	Koyuncu, Nursel
dc.date.accessioned	2020-11-25T09:44:21Z
dc.date.accessioned	2022-05-22T08:27:51Z
dc.date.available	2020-11-25T09:44:21Z
dc.date.available	2022-05-22T08:27:51Z
dc.date.issued	2020-06-25
dc.identifier.citation	Samuh, M. H., Al-Omari, A. I., & Koyuncu, N. (2020). Estimation of the Parameters of the New Weibull-Pareto Distribution Using Ranked Set Sampling. Statistica, 80(1), 103-123. https://doi.org/10.6092/issn.1973-2201/9368	en_US
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/7850
dc.description.abstract	The method of maximum likelihood estimation based on ranked set sampling (RSS) and some of its modifications is used to estimate the unknown parameters of the new Weibull-Pareto distribution. The estimators are compared with the conventional estimators based on simple random sampling (SRS). The biases, mean squared errors, and confidence intervals are used to the comparison. The effect of the set size and number of cycles of the RSS schemes are addressed. Monte Carlo simulation is carried out by using R. The results showed that the RSS estimators are more efficient than their competitors using SRS.	en_US
dc.language.iso	en	en_US
dc.publisher	Statistica	en_US
dc.subject	New Weibull-Pareto distribution	en_US
dc.subject	Fisher information	en_US
dc.subject	Maximum likelihood estimation	en_US
dc.subject	Ranked set sampling	en_US
dc.title	Estimation of the Parameters of the New Weibull-Pareto Distribution Using Ranked Set Sampling	en_US
dc.type	Article	en_US