Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species. © 2010 Published by Elsevier Ltd.
Data augmentation approach in Bayesian modelling of presence-only data / Fabio, Divino; Natalia, Golini; JONA LASINIO, Giovanna; Antti, Pettinen. - In: PROCEDIA ENVIRONMENTAL SCIENCES. - ISSN 1878-0296. - ELETTRONICO. - 7:(2011), pp. 38-43. ( 1st International Conference on Spatial Statistics 2011 Enschede 23-25 marzo 2011) [10.1016/j.proenv.2011.07.008].
Data augmentation approach in Bayesian modelling of presence-only data
JONA LASINIO, Giovanna;
2011
Abstract
Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species. © 2010 Published by Elsevier Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
