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apcf

R Package providing the Adapted Pair Correlation Function

https://github.com/rnuske/apcf

Science Score: 67.0%

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    CITATION.cff file
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    Found 5 DOI reference(s) in README
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    Low similarity (12.5%) to scientific vocabulary

Keywords

geo geos point-pattern-analysis r r-package spatial-statistics
Last synced: 6 months ago · JSON representation ·

Repository

R Package providing the Adapted Pair Correlation Function

Basic Info
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 3
Topics
geo geos point-pattern-analysis r r-package spatial-statistics
Created about 7 years ago · Last pushed 12 months ago
Metadata Files
Readme Changelog Citation

README.md

apcf: Adapted Pair Correlation Function

R-CMD-check Package-License CRAN Dependencies DOI <!-- badges: end -->

The apcf package provides a reimplementation of the Adapted Pair Correlation Function (Nuske et al. 2009) in C++. It relies heavily on the GEOS library and is enabled by Rcpp.

The Adapted Pair Correlation Function transfers the concept of the pair correlation function (PCF) from point patterns to patterns of objects of finite size and irregular shape (eg. lakes within a country). The pair correlation function describes the spatial distribution of objects. It assesses whether patterns are random, aggregated or regularly spaced. The PCF is non-cumulative and, thus, particularly suitable to reveal critical scales of the pattern.

The following figure shows three simulated patterns (regular, random, clustered; from Nuske et al. 2009) to demonstrate the behavior of the PCF in three extreme cases (colored line: estimated function; white line: theoretical value of the function under the null hypothesis of complete spatial randomness; grey area: 95% confidence envelope under the null hypothesis, computed by Monte Carlo simulation using 199 replicates). Under complete spatial randomness (CSR), g(r) = 1. Values g(r) < 1 suggest inhibition between objects and values g(r) > 1 suggest clustering.


Installation

The stable version can be installed from CRAN r install.packages("apcf")

and the development version is available from Github using the package remotes r remotes::install_github("rnuske/apcf")

Usage

The main steps are (i) the construction of nullmodels by randomizing the objects of the original pattern within the study area, (ii) the edge correction by determining the proportion of a buffer within the study area, and (iii) the calculation of the shortest distances between the objects.

```r

calculate distances between patches of original pattern and 3 nullmodels

number of nullmodels should by at least 199 and better yet 999

ds <- pat2dists(area=simarea, pattern=simpatreg, maxdist=25, n_sim=3)

derive PCF and envelope from distances

pcf <- dists2pcf(ds, r=0.2, rmax=25, stoyan=0.15, nrank=1)

plot PCF

plot(x=pcf, xlim=c(0, 20), ylim=c(0, 2.2)) ```

Requirements

For Unix-alikes GEOS (>= 3.4.0) is required. On Ubuntu bionic (18.04) and beyond one can install the dependency simply with sudo apt install libgeos-dev.

References

Nuske, R.S., Sprauer, S. and Saborowski, J. (2009): Adapting the pair-correlation function for analysing the spatial distribution of canopy gaps. Forest Ecology and Management 259(1): 107–116. https://doi.org/10.1016/j.foreco.2009.09.050

Owner

  • Name: Robert Nuske
  • Login: rnuske
  • Kind: user
  • Company: privat hier

Citation (CITATION.cff) 

cff-version: 1.2.0
title: 'apcf: Adapted Pair Correlation Function'
message: >-
  If you use the apcf package, please cite both the article
  from preferred-citation and the software itself.
type: software
authors:
  - family-names: Nuske
    given-names: Robert
    orcid: 'https://orcid.org/0000-0001-9773-2061'
identifiers:
  - type: doi
    value: 10.5281/zenodo.2535612
repository-code: 'https://github.com/rnuske/apcf'
url: 'https://rnuske.github.io/apcf/'
repository: 'https://CRAN.R-project.org/package=apcf'
abstract: >-
  The adapted pair correlation function transfers the
  concept of the pair correlation function from point
  patterns to patterns of objects of finite size and
  irregular shape (e.g. lakes within a country). The pair
  correlation function describes the spatial distribution of
  objects, e.g. random, aggregated or regularly spaced. This
  is a reimplementation of the method suggested by Nuske et
  al. (2009) using the library 'GEOS'.
license: GPL-3.0-or-later
version: 0.3.2
date-released: '2025-03-01'
preferred-citation:
  type: article
  title: >-
    Adapting the pair-correlation function for analysing the spatial
    distribution of canopy gaps
  authors:
    - family-names: Nuske
      given-names: Robert S.
    - family-names: Sprauer
      given-names: Susanne
    - family-names: Saborowski
      given-names: Joachim
  journal: Forest Ecology and Management
  volume: '259'
  issue: '1'
  year: '2009'
  doi: 10.1016/j.foreco.2009.09.050
  start: 107-116

GitHub Events

Total
  • Create event: 1
  • Release event: 1
  • Issues event: 1
  • Push event: 9
Last Year
  • Create event: 1
  • Release event: 1
  • Issues event: 1
  • Push event: 9

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 116
  • Total Committers: 4
  • Avg Commits per committer: 29.0
  • Development Distribution Score (DDS): 0.121
Past Year
  • Commits: 9
  • Committers: 2
  • Avg Commits per committer: 4.5
  • Development Distribution Score (DDS): 0.333
Top Committers
Name Email Commits
Robert Nuske r****e@n****e 102
Robert Nuske r****e@m****g 6
Robert Nuske r****e 5
Jeroen Ooms j****s@g****m 3
Committer Domains (Top 20 + Academic)
mailbox.org: 1 nw-fva.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 7
  • Total pull requests: 6
  • Average time to close issues: over 1 year
  • Average time to close pull requests: 3 days
  • Total issue authors: 2
  • Total pull request authors: 4
  • Average comments per issue: 1.0
  • Average comments per pull request: 2.67
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: about 11 hours
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • rnuske (6)
  • mdsumner (1)
Pull Request Authors
  • jeroen (3)
  • paleolimbot (1)
  • rnuske (1)
  • Nowosad (1)
Top Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 361 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 11
  • Total maintainers: 1
cran.r-project.org: apcf

Adapted Pair Correlation Function

  • Versions: 11
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 361 Last month
Rankings
Stargazers count: 21.1%
Forks count: 21.9%
Average: 27.6%
Dependent packages count: 29.8%
Downloads: 30.0%
Dependent repos count: 35.5%
Maintainers (1)
robert.nuske@mailbox.org
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.3.0 depends
  • Rcpp >= 0.12 imports
  • wk >= 0.6.0 imports
  • knitr * suggests
  • rmarkdown * suggests
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  • r-lib/actions/setup-pandoc v1 composite
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