scholarly journals Modified Power-Symmetric Distribution

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1410 ◽  
Author(s):  
Emilio Gómez-Déniz ◽  
Yuri A. Iriarte ◽  
Enrique Calderín-Ojeda ◽  
Héctor W. Gómez
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Normal Distribution ◽  
Method Of Moments ◽  
Simulation Analysis ◽  
Maximum Likelihood Estimators ◽  
Likelihood Estimation ◽  
Parameters Estimation ◽  
Symmetric Model ◽  
Symmetric Distributions

In this paper, a general class of modified power-symmetric distributions is introduced. By choosing as symmetric model the normal distribution, the modified power-normal distribution is obtained. For the latter model, some of its more relevant statistical properties are examined. Parameters estimation is carried out by using the method of moments and maximum likelihood estimation. A simulation analysis is accomplished to study the performance of the maximum likelihood estimators. Finally, we compare the efficiency of the modified power-normal distribution with other existing distributions in the literature by using a real dataset.

scholarly journals On estimation in multilevel models with block circular symmetric covariance structure

2012 ◽  
Vol 16 (1) ◽  
pp. 83-96
Author(s):  
Yuli Liang ◽  
Dietrich von Rosen ◽  
Tatjana von Rosen
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Parameter Space ◽  
Variance Components ◽  
Multilevel Model ◽  
Multilevel Models ◽  
Covariance Structure ◽  
Maximum Likelihood Estimators ◽  
Likelihood Estimation

In this article we consider a multilevel model with block circular symmetric covariance structure. Maximum likelihood estimation of the parameters of this model is discussed. We show that explicit maximum likelihood estimators of variance components exist under certain restrictions on the parameter space.

Optimization of Parameters Estimation for Normal Distribution Based on Bootstrap Method

2011 ◽  
Vol 52-54 ◽  
pp. 546-549
Author(s):  
Shi Bo Xin
Keyword(s):  
Maximum Likelihood ◽  
Normal Distribution ◽  
Maximum Likelihood Method ◽  
Simulation Analysis ◽  
Bootstrap Method ◽  
Parameters Estimation ◽  
Likelihood Method ◽  
Sample Mean ◽  
Optimization Of Parameters

According to sample mean submits normal distribution which is extracted from normal distribution, we give the equation of parameters estimation for normal distribution by bootstrap method, then we make a simulation analysis and compare the effect of parameters estimation which uses traditional maximum likelihood method and bootstrap method.

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