modelo                package:unknown                R Documentation

This function Estimate Probabilities via Maximum Entropy and computes the numeric value of area under the ROC curve (AUC) with the trapezoidal rule.

Description:

      Returns the probabilities that maximize the entropy conditional on a series of constraints that are linear in the features and the numeric value of area under the ROC curve (AUC) with the trapezoidal rule.
     	

Usage:

sdm.me(constr, states)

Arguments

constr 		vector of macroscopical constraints 
states 		vector, matrix or data frame of states (columns) and their attributes (rows).

Details:

     Species distribution models (SDMs) estimate the relationship between species records at sites and the environmental and/or spatial characteristics of those sites. 
       The principle of maximum entropy is 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).
       
Value:
       
            
       prob
       vector of predicted probabilities
       constr
       macroscopical constraints
       States
       percent
       states and their attributes
       whether the AUC is given in percent 
       
       
       
Author(s):

     Jorge Luiz Diaz Pinaya (jorge.pinaya@usp.br)


References:

     Further description of this approach can be found in: 

Steven J. Phillips, Miroslav Dudík, Robert E. Schapire.
A maximum entropy approach to species distribution modeling.
In Proceedings of the Twenty-First International Conference on Machine Learning, pages 655-662, 2004.

Steven J. Phillips, Robert P. Anderson, Robert E. Schapire
Maximum entropy modeling of species geographic distributions. 
Ecological Modelling, 190:231-259, 2006. 

Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudík, Yung En Chee, Colin J. Yates.
A statistical explanation of MaxEnt for ecologists. 
Diversity and Distributions, 17:43-57, 2011. 


Examples:

     ##