Logistic methods for resource selection functions and presence-only species distribution models

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2011, Pages 1384-1389

  Phillips, Steven J ^a   Elith, Jane ^b  

^a AT AND T LABS RESEARCH   (United States)

^b UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ADDITIVE MODELS; BOOSTED REGRESSION TREES; CONDITIONAL PROBABILITIES; DATA ASSUMPTION; ENVIRONMENTAL CONDITIONS; ENVIRONMENTAL VARIABLES; EXPECTATION-MAXIMIZATION APPROACHES; EXPONENTIAL MODELS; FUTURE CLIMATE; HABITAT LOSS; IDENTIFIABILITY; LOGISTIC MODELS; LOSS FUNCTIONS; MODELING FRAMEWORKS; MODELING TASK; NUMBER OF SPECIES; PROBABILITY ESTIMATE; RANDOM SAMPLE; REGRESSION MODEL; RESOURCE SELECTION FUNCTION; SPECIES DISTRIBUTION MODELS; STATISTICAL APPROACH; SURVEY DATA;

ARTIFICIAL INTELLIGENCE; BIODIVERSITY; CLIMATE CHANGE; ECOLOGY; ESTIMATION; POPULATION STATISTICS; PROBABILITY; REGRESSION ANALYSIS;

CLIMATE MODELS;

EID: 80055054109     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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