## Abstract

Ecological data often involve measurements taken at irregularly spaced locations (e.g., the heights of trees in a forest). A useful approach for modeling such data is via a marked point process, where the marks (i.e., measurements) and points (i.e., locations) are often assumed to be independent. Although this is a convenient assumption, it may not hold in practice. Schlather et al. (Journal of the Royal Statistical Society Services B, 66, 79-93, 2004) proposed a simulation-based approach to test this assumption. This paper presents a new method for testing the assumption of independence between the marks and the points. Instead of considering a simulation approach, we derive analytical results that allow the test to be implemented via a conventional χ^{2} statistic. We illustrate the use of our approach by applying it to an example involving desert plant data.

Original language | English (US) |
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Pages (from-to) | 101-111 |

Number of pages | 11 |

Journal | Environmental and Ecological Statistics |

Volume | 14 |

Issue number | 2 |

DOIs | |

State | Published - Jun 2007 |

## Keywords

- Conditional expectation of marks
- Subsampling

## ASJC Scopus subject areas

- Statistics and Probability
- Environmental Science(all)
- Statistics, Probability and Uncertainty