IDEAS home Printed from https://ideas.repec.org/a/bla/scjsta/v44y2017i2p324-345.html
   My bibliography  Save this article

Kernel Density Estimation on a Linear Network

Author

Listed:
  • Greg McSwiggan
  • Adrian Baddeley
  • Gopalan Nair

Abstract

No abstract is available for this item.

Suggested Citation

  • Greg McSwiggan & Adrian Baddeley & Gopalan Nair, 2017. "Kernel Density Estimation on a Linear Network," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(2), pages 324-345, June.
    • Handle: RePEc:bla:scjsta:v:44:y:2017:i:2:p:324-345
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/sjos.12255
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adrian Baddeley & Aruna Jammalamadaka & Gopalan Nair, 2014. "Multitype point process analysis of spines on the dendrite network of a neuron," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(5), pages 673-694, November.
    2. Barry, Ronald P. & McIntyre, Julie, 2011. "Estimating animal densities and home range in regions with irregular boundaries and holes: A lattice-based alternative to the kernel density estimator," Ecological Modelling, Elsevier, vol. 222(10), pages 1666-1672.
    3. Nicholas A. Som & Pascal Monestiez & Jay M. Ver Hoef & Dale L. Zimmerman & Erin E. Peterson, 2014. "Spatial sampling on streams: principles for inference on aquatic networks," Environmetrics, John Wiley & Sons, Ltd., vol. 25(5), pages 306-323, August.
    4. Luke Tierney, 2009. "Code analysis and parallelizing vector operations in R," Computational Statistics, Springer, vol. 24(2), pages 217-223, May.
    5. Ver Hoef, Jay M. & Peterson, Erin E., 2010. "A Moving Average Approach for Spatial Statistical Models of Stream Networks," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 6-18.
    6. 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).
    7. Qi Wei Ang & Adrian Baddeley & Gopalan Nair, 2012. "Geometrically Corrected Second Order Analysis of Events on a Linear Network, with Applications to Ecology and Criminology," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(4), pages 591-617, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matthias Eckardt & Jorge Mateu, 2021. "Second-order and local characteristics of network intensity functions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 318-340, June.
    2. Liu, Yang & Ruppert, David, 2021. "Density estimation on a network," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    3. 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.
    4. Yamazoe, Hiroya & Naito, Kanta, 2024. "Simultaneous confidence region of an embedded one-dimensional curve in multi-dimensional space," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).
    5. Matthias Eckardt & Mehdi Moradi, 2024. "Marked Spatial Point Processes: Current State and Extensions to Point Processes on Linear Networks," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(2), pages 346-378, June.
    6. Nicoletta D’Angelo & Giada Adelfio & Jorge Mateu, 2023. "Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks," Statistical Papers, Springer, vol. 64(3), pages 779-805, June.
    7. Arnone, Eleonora & Ferraccioli, Federico & Pigolotti, Clara & Sangalli, Laura M., 2022. "A roughness penalty approach to estimate densities over two-dimensional manifolds," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    8. Ottmar Cronie & Mehdi Moradi & Christophe A N Biscio, 2024. "A cross-validation-based statistical theory for point processes," Biometrika, Biometrika Trust, vol. 111(2), pages 625-641.

    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.
    1. Laura Anton-Sanchez & Pedro Larrañaga & Ruth Benavides-Piccione & Isabel Fernaud-Espinosa & Javier DeFelipe & Concha Bielza, 2017. "Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-14, June.
    2. Jakob G. Rasmussen & Heidi S. Christensen, 2021. "Point Processes on Directed Linear Networks," Methodology and Computing in Applied Probability, Springer, vol. 23(2), pages 647-667, June.
    3. Downs, Joni A. & Heller, Justin H. & Loraamm, Rebecca & Stein, Dana Oppenheim & McDaniel, Cassandra & Onorato, Dave, 2012. "Accuracy of home range estimators for homogeneous and inhomogeneous point patterns," Ecological Modelling, Elsevier, vol. 225(C), pages 66-73.
    4. Matthias Eckardt & Jorge Mateu, 2021. "Second-order and local characteristics of network intensity functions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 318-340, June.
    5. Barry, Ronald P. & McIntyre, Julie & Bernard, Jordan, 2024. "A geostatistical model based on random walks to krige regions with irregular boundaries and holes," Ecological Modelling, Elsevier, vol. 491(C).
    6. Matthias Eckardt & Mehdi Moradi, 2024. "Marked Spatial Point Processes: Current State and Extensions to Point Processes on Linear Networks," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(2), pages 346-378, June.
    7. Arii, Ken & Caspersen, John P. & Jones, Trevor A. & Thomas, Sean C., 2008. "A selection harvesting algorithm for use in spatially explicit individual-based forest simulation models," Ecological Modelling, Elsevier, vol. 211(3), pages 251-266.
    8. Jiao Jieying & Hu Guanyu & Yan Jun, 2021. "A Bayesian marked spatial point processes model for basketball shot chart," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 77-90, June.
    9. Frank Davenport, 2017. "Estimating standard errors in spatial panel models with time varying spatial correlation," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 155-177, March.
    10. Leandro, Camila & Jay-Robert, Pierre & Mériguet, Bruno & Houard, Xavier & Renner, Ian W., 2020. "Is my sdm good enough? insights from a citizen science dataset in a point process modeling framework," Ecological Modelling, Elsevier, vol. 438(C).
    11. Guangshun Bai & Xuemei Yang & Guangxin Bai & Zhigang Kong & Jieyong Zhu & Shitao Zhang, 2024. "Examining the Controls on the Spatial Distribution of Landslides Triggered by the 2008 Wenchuan Ms 8.0 Earthquake, China, Using Methods of Spatial Point Pattern Analysis," Sustainability, MDPI, vol. 16(16), pages 1-24, August.
    12. Vijay Rajagopal & Gregory Bass & Cameron G Walker & David J Crossman & Amorita Petzer & Anthony Hickey & Ivo Siekmann & Masahiko Hoshijima & Mark H Ellisman & Edmund J Crampin & Christian Soeller, 2015. "Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes," PLOS Computational Biology, Public Library of Science, vol. 11(9), pages 1-31, September.
    13. 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.
    14. Liao, Jinbao & Li, Zhenqing & Quets, Jan J. & Nijs, Ivan, 2013. "Effects of space partitioning in a plant species diversity model," Ecological Modelling, Elsevier, vol. 251(C), pages 271-278.
    15. Abdollah Jalilian, 2017. "Modelling and classification of species abundance: a case study in the Barro Colorado Island plot," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2401-2409, October.
    16. Éric Marcon & Florence Puech, 2023. "Mapping distributions in non-homogeneous space with distance-based methods [Cartographie des distributions dans un espace non homogène à l'aide de méthodes basées sur la distance]," Post-Print hal-04345149, HAL.
    17. Herguido Sevillano, E. & Lavado Contador, J.F. & Schnabel, S. & Pulido, M. & Ibáñez, J., 2018. "Using spatial models of temporal tree dynamics to evaluate the implementation of EU afforestation policies in rangelands of SW Spain," Land Use Policy, Elsevier, vol. 78(C), pages 166-175.
    18. Athanasios C. Micheas & Jiaxun Chen, 2018. "sppmix: Poisson point process modeling using normal mixture models," Computational Statistics, Springer, vol. 33(4), pages 1767-1798, December.
    19. Eric Marcon & Florence Puech, 2012. "A typology of distance-based measures of spatial concentration," Working Papers halshs-00679993, HAL.
    20. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.

    More about this item

    Statistics

    Access and download statistics

    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:44:y:2017:i:2:p:324-345. 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.