scholarly journals An Empirical Study on Maximum Likelihood Estimation of Missing Data by EM Algorithm

2018 ◽  
Vol 07 (02) ◽  
pp. 210-220
Author(s):  
镭 黎
Keyword(s):  
Missing Data ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Empirical Study ◽  
Em Algorithm ◽  
Likelihood Estimation ◽  
Estimation Of Missing Data

scholarly journals Maximum Likelihood Estimation using the EM Algorithm

2021 ◽  
Vol 8 (9) ◽  
pp. 275-277
Author(s):  
Ahsene Lanani
Keyword(s):  
Missing Data ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Em Algorithm ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Likelihood Estimation ◽  
Mixed Linear Model ◽  
Model Parameters ◽  
The Em Algorithm

This paper yields with the Maximum likelihood estimation using the EM algorithm. This algorithm is very used to solve nonlinear equations with missing data. We estimated the linear mixed model parameters and those of the variance-covariance matrix. The considered structure of this matrix is not necessarily linear. Keywords: Algorithm EM; Maximum likelihood; Mixed linear model.

Maximum-likelihood estimation in linkage heterogeneity models including additional information via the EM algorithm

1995 ◽  
Vol 12 (5) ◽  
pp. 515-527 ◽  
Author(s):  
Jeanine J. Houwing-Duistermaat ◽  
Lodewijk A. Sandkuijl ◽  
Arthur A. B. Bergen ◽  
Hans C. van Houwelingen
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Em Algorithm ◽  
Likelihood Estimation ◽  
Additional Information ◽  
The Em Algorithm
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