Fuzzy Similarity in Species Distributions
Overview
Functions to compute fuzzy versions of species occurrence patterns based on presence-absence data (including inverse distance interpolation, trend surface analysis, and prevalence-independent favourability obtained from probability of presence), as well as pair-wise fuzzy similarity (based on fuzzy logic versions of commonly used similarity indices) among those occurrence patterns. Includes also functions for model consensus and comparison (overlap and fuzzy similarity, fuzzy loss, fuzzy gain), and for data preparation, such as obtaining unique abbreviations of species names, defining the background region, cleaning and gridding (thinning) point occurrence data onto raster maps, selecting among (pseudo)absences to address survey bias, converting species lists (long format) to presence-absence tables (wide format), transposing part of a data frame, selecting relevant variables for models, assessing the false discovery rate, or analysing and dealing with multicollinearity. Initially described in Barbosa (2015) doi:10.1111/2041-210X.12372.
(Committed 2026-09-25)
Modified functions:
- selectAbsences
- fixed error when 'data' SpatVector and plot = TRUE
- cleanCoords
- added 'legend' argument (default NA for backward compatibility)
Other modified files:
- fuzsim.Rd
- mention Jaccard equivalence to Tanimoto index
- fuzzyRangeChange.Rd
- add Details section and simple 1-0 Examples to illustrate how it works
- clampVars.Rd
Show all changes in 4.60Hide the rest of the changes in 4.60
- recommend computing a clamping mask
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- WARNING12 OK, 1 WARNING2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 49includes a package overview page
- Examples that run
- 89%42 run in a plain check · 5 never run
- Exported functions with examples
- 96%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 65%
Downloads
Repository
- PRs merged (all time)
- not measured
- Median days to close, 50 most recently updated closed issues
- 6
- Median days to close, 50 most recently updated closed PRs
- not measured
Forks over time
Commits over time
3 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/ambarbosa/fuzzysim on 2026-10-18.
Funding links: GitHub Sponsors
The repository owner accepts GitHub Sponsors
Dependencies
Installing fuzzySim adds 10 packages (3 with compiled code, 20 MB of source tarballs). Heaviest: stringi 11 MB, performance 1.9 MB, Rcpp 1.8 MB.
Code & Tests
Datasets
People & History
Show 3 peopleHide 3 people
Pick two releases to compare their code metrics.
- 4.60Latest
- 4.592026-08-28 · diff ↗
- 4.542026-05-21 · diff ↗
- RR 4.6.0 released · 2026-04-24
- 4.502026-03-28 · diff ↗
- 4.482026-02-17 · diff ↗
- 4.462026-01-08 · diff ↗
- 4.382025-10-14 · diff ↗
- 4.362025-09-27 · diff ↗
- 4.342025-09-08 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 4.332025-03-21 · diff ↗
- 4.292024-12-13 · diff ↗
- 4.262024-10-30 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 4.10.72024-01-24 · diff ↗
Show 15 earlier eventsHide 15 earlier events
- 4.10.52023-10-09 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 4.9.92023-04-14 · diff ↗
- 4.9.82023-03-06 · diff ↗
- 4.9.22022-10-30 · diff ↗
- 4.32022-06-01 · diff ↗
- 4.02022-05-03 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 3.72022-01-21 · diff ↗
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 3.02020-02-04 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 2.02018-12-19
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-12-19
- Total releases
- 22 / 8 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 26 KB / 2 files
- Download size
- 156 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("fuzzySim")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.