Bayesian Modeling for Nonstationary Spatial Point Process via Spatial Deformations
Author:
Affiliation:
1. DME-Instituto de Matemática, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, RJ, Brazil
2. Instituto Nacional de Infectologia Evandro Chagas-FIOCRUZ, Rio de Janeiro 21040-360, RJ, Brazil
Abstract
Funder
Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq
Publisher
MDPI AG
Link
https://www.mdpi.com/1099-4300/26/8/678/pdf
Reference40 articles.
1. Diggle, P. (2013). Statistical Analysis of Spatial and Spatiotemporal Point Patterns, Taylor & Francis Inc.
2. Illian, J., Penttinen, A., Stoyan, H., and Stoyan, D. (2008). Statistical Analysis and Modelling of Spatial Point Patterns (Statistics in Practice), Wiley-Interscience.
3. A three-dimensional anisotropic point process characterization for pharmaceutical coatings;Rajala;Spat. Stat.,2017
4. Estimating Second-Order Characteristics of Inhomogeneous Spatio-Temporal Point Processes;Gabriel;Methodol. Comput. Appl. Probab.,2014
5. Hidden Second-order Stationary Spatial Point Processes;Hahn;Scand. J. Stat.,2016
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