Spatial ecology of perceived predation risk and vigilance behavior in white-faced capuchins
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
- 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.
- Roper Roy E. & Goodzey C., 2004. "Ecology of Fear," Journal of Homeland Security and Emergency Management, De Gruyter, vol. 1(2), pages 1-7, January.
- Davies, Tilman M. & Hazelton, Martin L. & Marshall, Jonathan. C, 2011. "sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i01).
- Ben T. Hirsch & Lesley J. Morrell, 2011. "Measuring marginal predation in animal groups," Behavioral Ecology, International Society for Behavioral Ecology, vol. 22(3), pages 648-656.
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.- 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.
- 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.
- Bouezmarni, Taoufik & Rombouts, Jeroen V.K., 2010.
"Nonparametric density estimation for positive time series,"
Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 245-261, February.
- BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V. K., 2006. "Nonparametric density estimation for positive time series," LIDAM Discussion Papers CORE 2006085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
- Giuseppe Espa & Giuseppe Arbia & Diego Giuliani, 2013. "Conditional versus unconditional industrial agglomeration: disentangling spatial dependence and spatial heterogeneity in the analysis of ICT firms’ distribution in Milan," Journal of Geographical Systems, Springer, vol. 15(1), pages 31-50, January.
- 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.
- Christopher S Fowler, 2018. "Key assumptions in multiscale segregation measures: How zoning and strength of spatial association condition outcomes," Environment and Planning B, , vol. 45(6), pages 1055-1072, November.
- 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.
- Jeffery Caroline & Ozonoff Al & White Laura Forsberg & Pagano Marcello, 2013. "Distance-Based Mapping of Disease Risk," The International Journal of Biostatistics, De Gruyter, vol. 9(2), pages 265-290, May.
- Nicoletta D'Angelo, 2025. "Detecting Changes in Space‐Varying Parameters of Local Poisson Point Processes," Environmetrics, John Wiley & Sons, Ltd., vol. 36(5), July.
- Nicolas Treich, 2022.
"The Dasgupta Review and the Problem of Anthropocentrism,"
Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(4), pages 973-997, December.
- Treich, Nicolas, 2022. "The Dasgupta Review and the problem of anthropocentrism," TSE Working Papers 126575, Toulouse School of Economics (TSE).
- Christoph Lambio & Tillman Schmitz & Richard Elson & Jeffrey Butler & Alexandra Roth & Silke Feller & Nicolai Savaskan & Tobia Lakes, 2023. "Exploring the Spatial Relative Risk of COVID-19 in Berlin-Neukölln," IJERPH, MDPI, vol. 20(10), pages 1-22, May.
- Mola-Yudego, Blas & Selkimäki, Mari & González-Olabarria, José Ramón, 2014. "Spatial analysis of the wood pellet production for energy in Europe," Renewable Energy, Elsevier, vol. 63(C), pages 76-83.
- Jeanne-Marie R. Stacciarini & Raffaele Vacca & Liang Mao, 2018. "Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research," IJERPH, MDPI, vol. 15(7), pages 1-17, June.
- 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.
- Pebesma, Edzer & Bivand, Roger & Ribeiro, Paulo Justiniano, 2015. "Software for Spatial Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i01).
- Peter Howe & Hilary Boudet & Anthony Leiserowitz & Edward Maibach, 2014. "Mapping the shadow of experience of extreme weather events," Climatic Change, Springer, vol. 127(2), pages 381-389, November.
- Yingqi Zhao & Donglin Zeng & Amy H. Herring & Amy Ising & Anna Waller & David Richardson & Michael R. Kosorok, 2011. "Detecting Disease Outbreaks Using Local Spatiotemporal Methods," Biometrics, The International Biometric Society, vol. 67(4), pages 1508-1517, December.
- François Sémécurbe & Cécile Tannier & Stéphane G. Roux, 2019. "Applying two fractal methods to characterise the local and global deviations from scale invariance of built patterns throughout mainland France," Journal of Geographical Systems, Springer, vol. 21(2), pages 271-293, June.
- Taylor, Benjamin M. & Davies, Tilman M. & Rowlingson, Barry S. & Diggle, Peter J., 2013. "lgcp: An R Package for Inference with Spatial and Spatio-Temporal Log-Gaussian Cox Processes," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i04).
- Davies, Tilman M. & Jones, Khair & Hazelton, Martin L., 2016. "Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 12-28.
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:oup:beheco:v:25:y:2014:i:3:p:477-486.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/beheco .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/oup/beheco/v25y2014i3p477-486..html