scholarly journals Minimum Divergence Estimators, Maximum Likelihood and the Generalized Bootstrap

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 185
Author(s):  
Michel Broniatowski
Keyword(s):  
Maximum Likelihood ◽  
Sampling Schemes ◽  
Minimum Divergence ◽  
Tests Of Fit

This paper states that most commonly used minimum divergence estimators are MLEs for suited generalized bootstrapped sampling schemes. Optimality in the sense of Bahadur for associated tests of fit under such sampling is considered.

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

2020 ◽  
Vol 9 (1) ◽  
pp. 189-203
Author(s):  
Abbas Eftekharian ◽  
Mostafa Razmkhah ◽  
Jafar Ahmadi
Keyword(s):  
Maximum Likelihood ◽  
Existence And Uniqueness ◽  
Sampling Methods ◽  
Scale Parameter ◽  
Likelihood Estimation ◽  
Ranked Set Sampling ◽  
Likelihood Estimator ◽  
Normal Distributions ◽  
Sampling Schemes ◽  
The Cost

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.

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.

Maximum likelihood procedure adapted to sampling schemes

1998 ◽  
Vol 70 (2) ◽  
pp. 277-286 ◽  
Author(s):  
Hirohisa Kishino ◽  
Avner Bar-Hen
Keyword(s):  
Maximum Likelihood ◽  
Sampling Schemes ◽  
Maximum Likelihood Procedure

scholarly journals Minimum divergence estimators, maximum likelihood and exponential families

2014 ◽  
Vol 93 ◽  
pp. 27-33 ◽  
Author(s):  
Michel Broniatowski
Keyword(s):  
Maximum Likelihood ◽  
Exponential Families ◽  
Minimum Divergence

Maximum Likelihood for Social Science

2018 ◽  
Author(s):  
Michael D. Ward ◽  
John S. Ahlquist
Keyword(s):  
Maximum Likelihood ◽  
Social Science
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