Maximum Likelihood Estimation

Known as: ML 
A method for estimating population characteristics based on limited data by choosing the sample values that make the data most likely to represent… (More)
National Institutes of Health

Papers overview

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Highly Cited
2010
Highly Cited
2010
Collaborative double robust targeted maximum likelihood estimators represent a fundamental further advance over standard targeted… (More)
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Highly Cited
2009
Highly Cited
2009
Image denoising is an important problem in image processing since noise may interfere with visual or automatic interpretation… (More)
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Highly Cited
2006
Highly Cited
2006
Genetic data are useful for estimating the genealogical relationship or relatedness between individuals of unknown ancestry. We… (More)
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Highly Cited
2005
Highly Cited
2005
Two major reasons for the popularity of the EM algorithm are that its maximum step involves only complete-data maximum likelihood… (More)
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Highly Cited
2005
Highly Cited
2005
A maximum likelihood method for inferring protein phylogeny was developed. It is based on a Markov model that takes into account… (More)
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Highly Cited
2002
Highly Cited
2002
We introduce and evaluate via a Monte Carlo study a robust new estimation technique that fits distribution functions to grouped… (More)
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Highly Cited
2002
Highly Cited
2002
We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and… (More)
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Highly Cited
2002
Highly Cited
2002
In this paper, a technique that is able to reconstruct highly sloped and discontinuous terrain height profiles, starting from… (More)
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Highly Cited
2001
Highly Cited
2001
In this study, EEG signals were analyzed using autoregressive (AR) method. Parameters in AR method were realized by using maximum… (More)
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Highly Cited
1999
Highly Cited
1999
Sparse coding is a method for finding a representation of data in which each of the components of the representation is only… (More)
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