Improved simultaneous monitoring of mean and coefficient of variation under ranked set sampling schemes

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.

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Effect of measurement error on exponentially weighted moving average control charts under ranked set sampling schemes

Journal of Statistical Computation and Simulation ◽

10.1080/00949655.2013.873040 ◽

2014 ◽

Vol 85 (6) ◽

pp. 1224-1246 ◽

Cited By ~ 28

Author(s):

Abdul Haq ◽

Jennifer Brown ◽

Elena Moltchanova ◽

Amer Ibrahim Al-Omari

Keyword(s):

Measurement Error ◽

Control Charts ◽

Moving Average ◽

Ranked Set Sampling ◽

Exponentially Weighted Moving Average ◽

Sampling Schemes ◽

Average Control ◽

Weighted Moving Average ◽

Exponentially Weighted

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Maximum likelihood estimation in location-scale families using varied L ranked set sampling

RAIRO - Operations Research ◽

10.1051/ro/2020124 ◽

2020 ◽

Author(s):

Amer Al-Omari

Keyword(s):

Maximum Likelihood ◽

Random Sampling ◽

Maximum Likelihood Estimators ◽

Likelihood Estimation ◽

Simple Random Sampling ◽

Ranked Set Sampling ◽

Sampling Schemes ◽

Scale Parameters ◽

Insight Into ◽

Family Of Distributions

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.

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Comparison of two sampling schemes in estimating the stress-strength reliability under the proportional reversed hazard rate model

Statistics Optimization & Information Computing ◽

10.19139/soic-2310-5070-781 ◽

2020 ◽

Vol 9 (1) ◽

pp. 82-98

Author(s):

Amineh Sadeghpour ◽

Ahmad Nezakati ◽

Mahdi Salehi

Keyword(s):

Hazard Rate ◽

Interval Estimation ◽

Minimum Variance ◽

Ranked Set Sampling ◽

Sampling Scheme ◽

Rate Model ◽

Data Set ◽

Reversed Hazard Rate ◽

Sampling Schemes ◽

Hazard Rate Model

In this paper, point and interval estimation of stress-strength reliability based on lower record ranked set sampling scheme under the proportional reversed hazard rate model are considered. Maximum likelihood, uniformly minimum variance unbiased, and Bayesian estimators of $\mathcal{R}$ are derived and their performances are compared. Various confidence intervals for the parameter $\mathcal{R}$ are constructed, and compared based on the simulation study. Moreover, the record ranked set sampling scheme is compared with ordinary records in case of interval estimations. Finally, a data set has been analyzed for illustrative purposes.

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