We summarize and discuss the current state of spatial point process theory and directions
for future research, making an analogy with generalized linear models and random effect …

This article is concerned with inference for a certain class of inhomogeneous Neyman–Scott
point processes depending on spatial covariates. Regression parameter estimates obtained …

Each chapter should be preceded by an abstract (10–15 lines long) that summarizes the
content. The abstract will appear online at www. SpringerLink. com and be available with …

The paper is concerned with parameter estimation for inhomogeneous spatial point
processes with a regression model for the intensity function and tractable second-order …

Point process models for spatio-temporal distance sampling data from a large-scale survey
of blue whales Page 1 The Annals of Applied Statistics 2017, Vol. 11, No. 4, 2270–2297 …

There is growing interest from research and conservation groups in the potential for using
small unoccupied aerial vehicles (UAVs;< 2 kg) to conduct wildlife surveys because they are …

We consider a fully model-based approach for the analysis of distance sampling data.
Distance sampling has been widely used to estimate abundance (or density) of animals or …

Precipitation has been regarded as one of the most important meteorological parameters
affecting human activities. The findings of research studies confirm that the variability and …

Online Supplementary Material for Bayesian Inference and Model Assessment for Spatial
Point Patterns Using Posterior Predictive Samples. Further analysis of the Duke Forest …

Abstract Species Distribution Models (SDMs) are used regularly to develop management
strategies, but many modelling methods ignore the spatial nature of data. To address this …