Parameter estimation under generalized ranked set sampling

1999 ◽  
Vol 42 (4) ◽  
pp. 353-360 ◽  
Author(s):  
YongHee Kim ◽  
Barry C. Arnold
Keyword(s):  
Parameter Estimation ◽  
Ranked Set Sampling

The efficiency of ranked set sampling for parameter estimation

2001 ◽  
Vol 53 (2) ◽  
pp. 189-199 ◽  
Author(s):  
Lucio Barabesi ◽  
Abdel El-Sharaawi
Keyword(s):  
Parameter Estimation ◽  
Ranked Set Sampling

scholarly journals Parameter Estimation Based on Double Ranked Set Samples with Applications to Weibull Distribution

2022 ◽  
Vol 19 (1) ◽  
pp. 2-24
Author(s):  
Mohamed Abd Elhamed Sabry ◽  
Hiba Zeyada Muhammed ◽  
Mostafa Shaaban ◽  
Abd El Hady Nabih
Keyword(s):  
Parameter Estimation ◽  
Weibull Distribution ◽  
Random Sampling ◽  
Likelihood Function ◽  
Maximum Likelihood Estimators ◽  
Simple Random Sampling ◽  
Ranked Set Sampling ◽  
Distribution Parameters ◽  
Two Parameters ◽  
Mean Square Errors

In this paper, the likelihood function for parameter estimation based on double ranked set sampling (DRSS) schemes is introduced. The proposed likelihood function is used for the estimation of the Weibull distribution parameters. The maximum likelihood estimators (MLEs) are investigated and compared to the corresponding ones based on simple random sampling (SRS) and ranked set sampling (RSS) schemes. A Monte Carlo simulation is conducted and the absolute relative biases, mean square errors, and efficiencies are compared for the different schemes. It is found that, the MLEs based on DRSS is more efficient than MLE using SRS and RSS for estimating the two parameters of the Weibull distribution (WD).

Weighted Combination of Prior and Sample Information and Parameter Estimation

Optimization ◽  
1976 ◽  
Vol 7 (5) ◽  
pp. 665-672
Author(s):  
H. Burke ◽  
C. Hennig ◽  
W H. Schmidt
Keyword(s):  
Parameter Estimation ◽  
Sample Information ◽  
Weighted Combination
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