Home > Research > Publications & Outputs > Detecting dependence between marks and location...

Research

Links

Text available via DOI:

View graph of relations

Detecting dependence between marks and locations of marked point processes.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Detecting dependence between marks and locations of marked point processes. / Diggle, Peter J.; Ribeiro, Paulo J.; Schlather, Martin S.
In: Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 66, No. 1, 01.02.2004, p. 79-93.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Diggle, PJ, Ribeiro, PJ & Schlather, MS 2004, 'Detecting dependence between marks and locations of marked point processes.', Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 66, no. 1, pp. 79-93. https://doi.org/10.1046/j.1369-7412.2003.05343.x

APA

Diggle, P. J., Ribeiro, P. J., & Schlather, M. S. (2004). Detecting dependence between marks and locations of marked point processes. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66(1), 79-93. https://doi.org/10.1046/j.1369-7412.2003.05343.x

Vancouver

Diggle PJ, Ribeiro PJ, Schlather MS. Detecting dependence between marks and locations of marked point processes. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 2004 Feb 1;66(1):79-93. doi: 10.1046/j.1369-7412.2003.05343.x

Author

Diggle, Peter J. ; Ribeiro, Paulo J. ; Schlather, Martin S. / Detecting dependence between marks and locations of marked point processes. In: Journal of the Royal Statistical Society: Series B (Statistical Methodology). 2004 ; Vol. 66, No. 1. pp. 79-93.

Bibtex

@article{fc2bee058e3e462f960bb53fa46ededc,
title = "Detecting dependence between marks and locations of marked point processes.",
abstract = "We introduce two characteristics for stationary and isotropic marked point proces- ses, E(h) and V(h), and describe their use in investigating mark–point interactions. These quantities are functions of the interpoint distance h and denote the conditional expectation and the conditional variance of a mark respectively, given that there is a further point of the process a distance h away. We present tests based on E and V for the hypothesis that the values of the marks can be modelled by a random field which is independent of the unmarked point process. We apply the methods to two data sets in forestry.",
author = "Diggle, {Peter J.} and Ribeiro, {Paulo J.} and Schlather, {Martin S.}",
note = "RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research",
year = "2004",
month = feb,
day = "1",
doi = "10.1046/j.1369-7412.2003.05343.x",
language = "English",
volume = "66",
pages = "79--93",
journal = "Journal of the Royal Statistical Society: Series B (Statistical Methodology)",
issn = "1369-7412",
publisher = "Wiley-Blackwell",
number = "1",

}

RIS

TY - JOUR

T1 - Detecting dependence between marks and locations of marked point processes.

AU - Diggle, Peter J.

AU - Ribeiro, Paulo J.

AU - Schlather, Martin S.

N1 - RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research

PY - 2004/2/1

Y1 - 2004/2/1

N2 - We introduce two characteristics for stationary and isotropic marked point proces- ses, E(h) and V(h), and describe their use in investigating mark–point interactions. These quantities are functions of the interpoint distance h and denote the conditional expectation and the conditional variance of a mark respectively, given that there is a further point of the process a distance h away. We present tests based on E and V for the hypothesis that the values of the marks can be modelled by a random field which is independent of the unmarked point process. We apply the methods to two data sets in forestry.

AB - We introduce two characteristics for stationary and isotropic marked point proces- ses, E(h) and V(h), and describe their use in investigating mark–point interactions. These quantities are functions of the interpoint distance h and denote the conditional expectation and the conditional variance of a mark respectively, given that there is a further point of the process a distance h away. We present tests based on E and V for the hypothesis that the values of the marks can be modelled by a random field which is independent of the unmarked point process. We apply the methods to two data sets in forestry.

U2 - 10.1046/j.1369-7412.2003.05343.x

DO - 10.1046/j.1369-7412.2003.05343.x

M3 - Journal article

VL - 66

SP - 79

EP - 93

JO - Journal of the Royal Statistical Society: Series B (Statistical Methodology)

JF - Journal of the Royal Statistical Society: Series B (Statistical Methodology)

SN - 1369-7412

IS - 1

ER -