Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Guan, Yongtao & Loh, Ji Meng, 2007. "A Thinned Block Bootstrap Variance Estimation Procedure for Inhomogeneous Spatial Point Patterns," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1377-1386, December.
- Cao, R., 1993. "Bootstrapping the Mean Integrated Squared Error," Journal of Multivariate Analysis, Elsevier, vol. 45(1), pages 137-160, April.
- Lionel Cucala, 2008. "Intensity Estimation for Spatial Point Processes Observed with Noise," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(2), pages 322-334, June.
- Peter Diggle, 1985. "A Kernel Method for Smoothing Point Process Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(2), pages 138-147, June.
- Guan, Yongtao, 2008. "On Consistent Nonparametric Intensity Estimation for Inhomogeneous Spatial Point Processes," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1238-1247.
- Rasmus Plenge Waagepetersen, 2007. "An Estimating Function Approach to Inference for Inhomogeneous Neyman–Scott Processes," Biometrics, The International Biometric Society, vol. 63(1), pages 252-258, March.
- Yongtao Guan, 2008. "A goodness-of-fit test for inhomogeneous spatial Poisson processes," Biometrika, Biometrika Trust, vol. 95(4), pages 831-845.
- Brooks, Maria Mori & Marron, J. Stephen, 1991. "Asymptotic optimality of the least-squares cross-validation bandwidth for kernel estimates of intensity functions," Stochastic Processes and their Applications, Elsevier, vol. 38(1), pages 157-165, June.
- Tarn Duong & Martin L. Hazelton, 2005. "Cross‐validation Bandwidth Matrices for Multivariate Kernel Density Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(3), pages 485-506, September.
- Yongtao Guan, 2007. "A Composite Likelihood Cross‐validation Approach in Selecting Bandwidth for the Estimation of the Pair Correlation Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(2), pages 336-346, June.
- Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
- Cao, Ricardo & Cuevas, Antonio & Gonzalez Manteiga, Wensceslao, 1994. "A comparative study of several smoothing methods in density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 17(2), pages 153-176, February.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Federico Ferraccioli & Eleonora Arnone & Livio Finos & James O. Ramsay & Laura M. Sangalli, 2021. "Nonparametric density estimation over complicated domains," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(2), pages 346-368, April.
- Ignacio González-Pérez & María Isabel Borrajo & Wenceslao González-Manteiga, 2025. "Nonparametric testing of first-order structure in point processes on linear networks," Statistical Papers, Springer, vol. 66(2), pages 1-38, February.
- M. N. M. Lieshout, 2020. "Infill Asymptotics and Bandwidth Selection for Kernel Estimators of Spatial Intensity Functions," Methodology and Computing in Applied Probability, Springer, vol. 22(3), pages 995-1008, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Borrajo, M.I. & González-Manteiga, W. & Martínez-Miranda, M.D., 2020. "Bootstrapping kernel intensity estimation for inhomogeneous point processes with spatial covariates," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
- Yu Ryan Yue & Ji Meng Loh, 2011. "Bayesian Semiparametric Intensity Estimation for Inhomogeneous Spatial Point Processes," Biometrics, The International Biometric Society, vol. 67(3), pages 937-946, September.
- Borrajo, M.I. & González-Manteiga, W. & Martínez-Miranda, M.D., 2024. "Goodness-of-fit test for point processes first-order intensity," Computational Statistics & Data Analysis, Elsevier, vol. 194(C).
- Ute Hahn & Eva B. Vedel Jensen, 2016. "Hidden Second-order Stationary Spatial Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 455-475, June.
- Nicoletta D’Angelo & Marianna Siino & Antonino D’Alessandro & Giada Adelfio, 2022. "Local spatial log-Gaussian Cox processes for seismic data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 633-671, December.
- Jesper Møller & Carlos Díaz‐Avalos, 2010. "Structured Spatio‐Temporal Shot‐Noise Cox Point Process Models, with a View to Modelling Forest Fires," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 2-25, March.
- Davidson, Marty, 2024. "Strategic Point Processes," OSF Preprints g5r9t, Center for Open Science.
- repec:osf:osfxxx:g5r9t_v1 is not listed on IDEAS
- Frédéric Lavancier & Ronan Le Guével, 2021. "Spatial birth–death–move processes: Basic properties and estimation of their intensity functions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 798-825, September.
- Barbeito, Inés & Cao, Ricardo, 2016. "Smoothed stationary bootstrap bandwidth selection for density estimation with dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 130-147.
- M. N. M. Lieshout, 2020. "Infill Asymptotics and Bandwidth Selection for Kernel Estimators of Spatial Intensity Functions," Methodology and Computing in Applied Probability, Springer, vol. 22(3), pages 995-1008, September.
- Yongtao Guan, 2008. "Variance estimation for statistics computed from inhomogeneous spatial point processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 175-190, February.
- Roba Bairakdar & Debbie Dupuis & Melina Mailhot, 2024. "Deviance Voronoi Residuals for Space-Time Point Process Models: An Application to Earthquake Insurance Risk," Papers 2410.04369, arXiv.org.
- Nicoletta D'Angelo, 2025. "Detecting Changes in Space‐Varying Parameters of Local Poisson Point Processes," Environmetrics, John Wiley & Sons, Ltd., vol. 36(5), July.
- Gril, Lorena & Rendtel, Ulrich, 2026. "Mapping high-income taxpayers in Berlin using kernel-smoothed proportions from aggregated georeferenced data," Discussion Papers 2026/2, Free University Berlin, School of Business & Economics.
- Ji Meng Loh & Woncheol Jang, 2010. "Estimating a cosmological mass bias parameter with bootstrap bandwidth selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 761-779, November.
- Yehua Li & Yongtao Guan, 2014. "Functional Principal Component Analysis of Spatiotemporal Point Processes With Applications in Disease Surveillance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1205-1215, September.
- Mohammad Ghorbani & Nafiseh Vafaei & Mari Myllymäki, 2025. "A kernel-based test for the first-order separability of spatio-temporal point processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 34(3), pages 580-611, September.
- García-Portugués, Eduardo & Crujeiras, Rosa M. & González-Manteiga, Wenceslao, 2013. "Kernel density estimation for directional–linear data," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 152-175.
- M. N. M. Lieshout, 2024. "Non-parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(2), pages 313-331, April.
- Heiler, Siegfried & Feng, Yuanhua, 1997. "A bootstrap bandwidth selector for local polynomial fitting," Discussion Papers, Series II 344, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:scjsta:v:43:y:2016:i:2:p:416-435. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0303-6898 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/bla/scjsta/v43y2016i2p416-435.html