A flexible ranked set sampling schemes: Statistical analysis on scale parameter

Abstract

A flexible ranked set sampling scheme including some various existing sampling methods is proposed. This scheme may be used to minimize the error of ranking and the cost of sampling. Based on the data obtained from this scheme, the maximum likelihood estimation as well as the Fisher information are studied for the scale family of distributions. The existence and uniqueness of the maximum likelihood estimator of the scale parameter of the exponential and normal distributions are investigated. Moreover, the optimal scheme is derived via simulation and numerical computations.

Generalized Exponential Distribution - Estimation of parameters using modifications in methods of Ranked Set Sampling

“…Al-Odat and Al-Saleh (2001) introduced the concept of varied size RSS, which is known as Moving Extreme Ranked Set Sampling. Eftekharian and Razmkhah (2016) discussed the unified ranked set sampling scheme to estimate the population mean and Eftekharian et al (2021) discussed the flexible ranked set sampling scheme to estimate scale parameters of the exponential and normal distributions.…”

Estimation Study of Multicomponent Stress-Strength Reliability Using Advanced Sampling Approach

“…Reference [12] presented and explored parameter estimators for the RSS scheme's two-parameter inverted Topp-Leone distribution. The scale family of distributions' maximum likelihood (ML) estimator and some RSS techniques were studied in [13]. Reference [14] considered an application to real data, it was suggested to use RSS to enhance estimate of the inverted Kumaraswamy distribution parameters.…”