Two steps generalized maximum entropy estimation procedure for fitting linear regression when both covariates are subject to error

2014 ◽  
Vol 41 (8) ◽  
pp. 1708-1720
Author(s):  
Amjad D. Al-Nasser
Keyword(s):  
Linear Regression ◽  
Maximum Entropy ◽  
Estimation Procedure ◽  
Entropy Estimation ◽  
Generalized Maximum Entropy ◽  
Maximum Entropy Estimation

scholarly journals Generalized Maximum Entropy Estimation of Linear Models

2017 ◽  
Vol 17 (1) ◽  
pp. 240-249 ◽  
Author(s):  
Paul Corral ◽  
Daniel Kuehn ◽  
Ermengarde Jabir
Keyword(s):  
Maximum Likelihood ◽  
Maximum Entropy ◽  
Linear Models ◽  
Estimation Method ◽  
Information Theoretic ◽  
Entropy Estimation ◽  
Generalized Maximum Entropy ◽  
Maximum Entropy Estimation ◽  
Distributional Assumptions ◽  
Highly Correlated

In this article, we describe the user-written gmentropylinear command, which implements the generalized maximum entropy estimation method for linear models. This is an information-theoretic procedure preferable to its maximum likelihood counterparts in many applications; it avoids making distributional assumptions, works well when the sample is small or covariates are highly correlated, and is more efficient than its maximum likelihood equivalent. We give a brief introduction to the generalized maximum entropy procedure, present the gmentropylinear command, and give an example using the command.

scholarly journals Comparison of entropy measures in generalized maximum entropy estimation

2018 ◽  
Vol 1053 ◽  
pp. 012021
Author(s):  
Wilawan Srichaikul ◽  
Woraphon Yamaka ◽  
Paravee Maneejuk ◽  
Songsak Sriboonchitta
Keyword(s):  
Maximum Entropy ◽  
Entropy Estimation ◽  
Generalized Maximum Entropy ◽  
Entropy Measures ◽  
Maximum Entropy Estimation
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