Generalized Maximum Entropy Estimation of Linear Models
2017 ◽
Vol 17
(1)
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pp. 240-249
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Keyword(s):
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.
2004 ◽
pp. 199-234
◽
2014 ◽
Vol 21
(5)
◽
pp. 395-409
◽
2015 ◽
Vol 15
(2)
◽
pp. 512-522
◽
2018 ◽
Vol 1053
◽
pp. 012021