The DOI matches its Crossref record.
A model for clustering
Abstract
A number of tests are available for the null hypothesis that a set of points in a region are scattered randomly, but relatively little is known about forms for the alternative. It is shown that under certain assumptions, the most severe of which is of Markov type, the probability density of the points must be of a simple explicit form depending on a single clustering parameter. The estimation of the parameter is studied and illustrated with an example.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Ripley, B. D. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01615.x · Cited by 2,511
The second-order analysis of stationary point processes
Ripley, B. D. (1976) · Journal of Applied Probability · doi:10.2307/3212829 · Cited by 1,539
Hybrids of gibbs point process models and their implementation
Baddeley, A., Turner, R., Mateu, J., & Bevan, A. (2013) · Journal of Statistical Software · doi:10.18637/jss.v055.i11 · Cited by 52
Metadata
- Authors
- STRAUSS, D. J.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1975-08-01
- Volume
- 62
- Issue
- 2
- Pages
- 467-475
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2037590223
- Cited by
- 416
- References
- 0
- FWCI
- 4.22
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A model for clustering. https://app.cochat.ai/papers/10.1093/biomet/62.2.467
- The paper
- STRAUSS, D. J. (1975). A model for clustering. Biometrika. https://doi.org/10.1093/biomet/62.2.467
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
