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Maxent Applied To Linear Regression
1990Given sparse, unreplicated data of poor instrumental resolution, we determine the probability of linear models using orthogonal least squares regression and MAXENT with an ‘expert draftsman’ constraint. An information bound condition enables MAXENT inference for the reliability of evidence determining the probability distribution for observations of a ...
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Application of Maxent to Inverse Photoemission Spectroscopy
1996Information about the spectral density gained by inverse photoemission spectroscopy is distorted by the Fermi distribution and the apparatus function. In many cases recovery of the desired physical quantities is hampered by an ill-posed inversion problem.
W. von der Linden +2 more
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Evaluating sampling bias correction methods for invasive species distribution modeling in Maxent
Ecological Informatics, 2023Frederic Sorbe +2 more
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Mapping cropland suitability in China using optimized MaxEnt model
Field crops research (Print), 2023Xiaolian Li +5 more
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Quantified Maxent: An NMR Application
1990‘Classic MaxEnt’ is a Bayesian derivation of the MaxEnt treatment of inverse problems leading to a posterior probability ‘bubble’ over the solution. This probability bubble—which is maximised at the optimal regularised solution—provides the framework for quantitative inferences about the solution.
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MaxEnt Principle for Handling Uncertainty with Qualitative Values
AIP Conference Proceedings, 2006Bayesian mathematical model is the oldest method for modelling subjective degree of belief. If we have probabilistic measures with unknown values, then we must choose a different and appropriate model. The belief functions are a bridge between various models handling different forms of uncertainty.
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