Volume 55, 2021Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
|Page(s)||S2759 - S2771|
|Published online||02 March 2021|
Maximum likelihood estimation in location-scale families using varied L ranked set sampling
Department of Mathematics, Faculty of Science, Al Al-Bayt University, Mafraq 25113, Jordan
* Corresponding author: email@example.com
Accepted: 28 October 2020
Recently, a generalized ranked set sampling (RSS) scheme has been introduced which encompasses several existing RSS schemes, namely varied L RSS (VLRSS), and it provides more precise estimators of the population mean than the estimators with the traditional simple random sampling (SRS) and RSS schemes. In this paper, we extend the work and consider the maximum likelihood estimators (MLEs) of the location and scale parameters when sampling from a location-scale family of distributions. In order to give more insight into the performance of VLRSS with respect to SRS and RSS schemes, the asymptotic relative precisions of the MLEs using VLRSS relative to that using SRS and RSS are compared for some usual location-scale distributions. It turns out that the MLEs with VLRSS are more precise than those with the existing sampling schemes.
Mathematics Subject Classification: 62D05
Key words: Asymptotic relative precision / fisher information / location-scale family / maximum likelihood estimator / simple random sampling / varied L ranked set sampling
© EDP Sciences, ROADEF, SMAI 2021
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