Maximum entropy modeling of species geographic distributions
Citations
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5,314 citations
Cites methods from "Maximum entropy modeling of species..."
...Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation...
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5,076 citations
Cites background or methods from "Maximum entropy modeling of species..."
...…Frescino 2002), classification and regression trees and ensembles of trees (random forests: Prasad et al. 2006; boosted regression trees: Elith et al. 2008), genetic algorithms (Stockwell & Peters 1999), support vector machines (Drake et al. 2006), and maximum entropy models (Phillips et al. 2006)....
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...Where analytical methods were once restricted to envelopes and distance measures, comparison of presence records with background or pseudoabsence points is now common (e.g., using GARP, ENFA, MaxEnt, and regression methods)....
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...In machine learning these ideas of model selection and tuning are termed “regularization,” i.e., making the fitted surface more regular or smooth by controlling overfitting (e.g., used in MaxEnt, Phillips et al. 2006)....
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...The key structural features of GLMs (non-normal error distributions, additive terms, nonlinear fitted functions) continue to be useful and are part of many current methods including RSFs (Manly et al. 2002) and maximum entropy models (MaxEnt; Phillips et al. 2006)....
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4,621 citations
Cites background or methods from "Maximum entropy modeling of species..."
...MaxEnt (Phillips et al., 2006; Phillips & Dudı́k, 2008) is one such method and is the focus of this paper....
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...…or coefficients These are the parameters of the model that weight the contribution of each feature. k in previous papers*, b in this paper *Phillips et al. (2006), Phillips & Dudı́k (2008) 48 Diversity and Distributions, 17, 43–57, ª 2010 Blackwell Publishing Ltd tuning parameter k.…...
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...Note also that the AUC in this case is calculated on presence vs. background data (Phillips et al., 2006)....
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...This was called the ‘‘raw’’ distribution (Phillips et al., 2006), and gave the probability, given the species is present, that it is found at pixel x. Maximizing the entropy of the raw distribution is equivalent to minimizing the relative entropy of f1(z) relative to f(z), so the two formulations…...
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...The MaxEnt model – a short overview Previous papers have described MaxEnt as estimating a distribution across geographic space (Phillips et al., 2006; Phillips & Dudı́k, 2008)....
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References
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"Maximum entropy modeling of species..." refers methods in this paper
...ROC analysis was developed in signal processing and is widely used in clinical medicine(Hanley and McNeil, 1982, 1983; Zweig and Campbell, 1993)....
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...Each partition was created by randomly selecting 70% of the occurrence localities as training data, with the remaining 30% reserved for testing the resulting models....
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16,496 citations
"Maximum entropy modeling of species..." refers methods in this paper
...It uses a non-parametric test(DeLong et al., 1988)to determine whether one prediction is significantly better than another when using correlated samples (i.e., with both predictions evaluated on the same test instances), and reports the result as aχ2 statistic and correspondingp value....
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12,099 citations
"Maximum entropy modeling of species..." refers background in this paper
...Its origins lie in statistical mechanics (Jaynes, 1957) , and it remains an active area of research with an Annual Conference, Maximum Entropy and Bayesian Methods, that explores applications in diverse areas such as astronomy, portfolio optimization, image reconstruction, statistical physics and signal processing....
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...Jaynes gave a general answer to this question: the best approach is to ensure that the approximation satisfies any constraints on the unknown distribution that we are aware of, and that subject to those constraints, the distribution should have maximum entropy(Jaynes, 1957) ....
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...E.T. Jaynes gave a general answer to this question: the best approach is to ensure that the approximation satisfies any constraints on the unknown distribution that we are aware of, and that subject to those constraints, the distribution should have maximum entropy(Jaynes, 1957)....
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...Its origins lie in statistical mechanics(Jaynes, 1957), and it remains an active area of research with an Annual Conference, Maximum Entropy and Bayesian Methods, that explores applications in diverse areas such as astronomy, portfolio optimization, image reconstruction, statistical physics and…...
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7,089 citations
"Maximum entropy modeling of species..." refers background in this paper
...This is important for applications such as invasive-species management (e.g.,Peterson and Robins, 2003) and predicting the impact of climate change (e.g.,Thomas et al., 2004)....
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