Parametric estimation of location and scale parameters in ranked set sampling

2011 ◽  
Vol 141 (4) ◽  
pp. 1616-1622 ◽  
Author(s):  
Omer Ozturk
Keyword(s):  
Ranked Set Sampling ◽  
Parametric Estimation ◽  
Scale Parameters

On the Efficiency of Ranked Set Sampling Strategies in Parametric Estimation

1997 ◽  
Vol 47 (1-2) ◽  
pp. 23-42 ◽  
Author(s):  
Dayong Li ◽  
Nora Ni Chuiv
Keyword(s):  
Random Sample ◽  
Ranked Set Sampling ◽  
Parametric Estimation ◽  
Simple Random Sample ◽  
Sampling Strategies ◽  
Ranked Set Sample ◽  
Estimation Problems ◽  
Parameters Of Interest

In this paper we discuss the issue of efficiency of a ranked set sample compared to a simple random sample in the context of a variety of parametric estimation problems. We establish that the use of appropriate variations of a ranked set sample often results in improved estimation of many common parameters of interest with a substantially smaller number of measurements compared to a simple random sample.

scholarly journals Effectivity of Modified Maximum Likelihood Estimators Using Selected Ranked Set Sampling Data

2016 ◽  
Vol 38 (2) ◽  
Author(s):  
Tamanna Islam ◽  
Molla Rahman Shaibur ◽  
S.S. Hossain
Keyword(s):  
Maximum Likelihood ◽  
Ranked Set Sampling ◽  
Simple Random Sample ◽  
Exponential Distributions ◽  
Underlying Distribution ◽  
Population Mean ◽  
Scale Parameters ◽  
Modified Maximum Likelihood ◽  
Two Parameter ◽  
Better Than

This paper describes the modified maximum likelihood estimator (MMLE) of location and scale parameters based on selected ranked set sampling (SRSS) for normal, uniform and two-parameter exponential distributions. For these distributions, the MMLE of location and scale parameters for SRSS data were compared with the estimators of location and scale parameters for simple random sample (SRS) and ranked set sample (RSS). The MMLE based on SRSS data were found to be advantageous as compared to SRS and RSS estimators for the same number of measurements. The SRSS method with errors in ranking was also described. The minimum correlation between the actual and erroneous ranking was required for MMLE of SRSS to achieve better precision than usual SRS and RSS estimators. When the wrong assumption about the underlying distribution was present, the MMLE of the population mean based on SRSS was better than the RSS estimator ofthe population mean for all the cases considered.

scholarly journals An asymptotic measure of accuracy effect from censorship in parametric estimation

2003 ◽  
Vol 34 (2) ◽  
pp. 189-195
Author(s):  
Chung-Siung Kao
Keyword(s):  
Censored Data ◽  
Parametric Estimation ◽  
Scale Parameters ◽  
Data Value

An asymptotic measure is provided to evaluate the effect on loss of accuracy for censored data in parametric estimation of location and scale parameters. With this measure, it is shown that the amount of effect from censored data relative to noncensored data is invariant of the actual values of the location and scale parameters, but is only dependent on the form of underlying distributions which the data are originated. In addition, among the most well-known distributions, obtained results for the measure show that two censored data values together usually may possess more information than one noncensored data value in the parametric estimation for location and scale parameters.

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

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.

scholarly journals New Parametric Estimation Methods based on Ranked Set Sampling

2019 ◽  
Vol 32 (4) ◽  
pp. 1356-1368
Author(s):  
Mohamed ABDALLAH ◽  
Samir ASHOUR
Keyword(s):  
Ranked Set Sampling ◽  
Parametric Estimation ◽  
Estimation Methods
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