Large sample properties of modified maximum likelihood estimator of the location parameter using moving extremes ranked set sampling

Han Wang and Wangxue Chen

Statistics & Probability Letters, 2025, vol. 223, issue C

Abstract: The maximum likelihood estimator (MLE) obtained using moving extremes ranked set sampling (MERSS) typically does not have a closed form expression. In this study, we investigate a modified MLE (MMLE) utilizing MERSS for estimating the location parameter of a location family and analyze its properties in large samples. We derive the explicit form of the MMLE for two common distributions when MERSS is employed. The numerical results from two usual distributions indicate that the MMLE using MERSS is more efficient than that the MLE using simple random sampling with an equivalent sample size. The numerical results also indicate the loss of efficiency in using the MMLE under MERSS instead of the MLE under MERSS is very small for small values of m. Additionally, we examine the implications of imperfect ranking and demonstrate our approach using a real dataset.

Keywords: Moving extremes ranked set sampling; Modified maximum likelihood estimator; Asymptotic normality (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.spl.2025.110430

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