Poisson point process models solve the ``pseudo-absence problem for presence-only data in ecology

DOI10.1214/10-AOAS331zbMath1202.62171arXiv1011.3319WikidataQ57239187 ScholiaQ57239187MaRDI QIDQ614153

Leah C. Shepherd, David I. Warton

Publication date: 27 December 2010

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1011.3319

zbMATH Keywords

habitat modelingoccurrence datapseudo-absencesquadrature pointsspecies distribution modeling

Mathematics Subject Classification ID

Related Items (19)

Penalized composite likelihoods for inhomogeneous Gibbs point process models ⋮ Fast, Approximate Maximum Likelihood Estimation of Log-Gaussian Cox Processes ⋮ Hierarchical animal movement models for population‐level inference ⋮ Finite-sample equivalence in statistical models for presence-only data ⋮ Infinitely imbalanced binomial regression and deformed exponential families ⋮ Modelling and classification of species abundance: a case study in the Barro Colorado Island plot ⋮ Additive multivariate Gaussian processes for joint species distribution modeling with heterogeneous data ⋮ Temporal variation and scale in movement-based resource selection functions ⋮ Computationally efficient statistical differential equation modeling using homogenization ⋮ Predicting the Geographic Distribution of a Species from Presence‐Only Data Subject to Detection Errors ⋮ Leverage and Influence Diagnostics for Spatial Point Processes ⋮ Correction note: Poisson point process models solve the ``pseudo-absence problem for presence-only data in ecology ⋮ Analysis of presence-only data via exact Bayes, with model and effects identification ⋮ A general theory for preferential sampling in environmental networks ⋮ Multi-species distribution modeling using penalized mixture of regressions ⋮ Estimating animal utilization distributions from multiple data types: a joint spatiotemporal point process framework ⋮ Efficient modelling of presence-only species data via local background sampling ⋮ Continuous-time discrete-space models for animal movement ⋮ Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology

Uses Software

• R
• spatstat
• VEGAS

Cites Work

• A new algorithm for adaptive multidimensional integration
• Area-interaction point processes
• Presence‐Only Data and the EM Algorithm
• Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
• Model Selection and Multimodel Inference
• Approximating Point Process Likelihoods with GLIM
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