Package: opticut 0.1-3

opticut: Likelihood Based Optimal Partitioning and Indicator Species Analysis

Likelihood based optimal partitioning and indicator species analysis. Finding the best binary partition for each species based on model selection, with the possibility to take into account modifying/confounding variables as described in Kemencei et al. (2014) <doi:10.1556/ComEc.15.2014.2.6>. The package implements binary and multi-level response models, various measures of uncertainty, Lorenz-curve based thresholding, with native support for parallel computations.

Authors:Peter Solymos [cre, aut], Ermias T. Azeria [ctb]

opticut_0.1-3.tar.gz
opticut_0.1-3.zip(r-4.5)opticut_0.1-3.zip(r-4.4)opticut_0.1-3.zip(r-4.3)
opticut_0.1-3.tgz(r-4.4-any)opticut_0.1-3.tgz(r-4.3-any)
opticut_0.1-3.tar.gz(r-4.5-noble)opticut_0.1-3.tar.gz(r-4.4-noble)
opticut_0.1-3.tgz(r-4.4-emscripten)opticut_0.1-3.tgz(r-4.3-emscripten)
opticut.pdf |opticut.html✨
opticut/json (API)

# Install 'opticut' in R:

install.packages('opticut', repos = c('https://psolymos.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/psolymos/opticut/issues

Datasets:

birdrec - Bird Species Detections
dolina - Land Snail Data Set
warblers - Warblers Data Set

On CRAN:

ecology indicator-species-analysis likelihood optimal-partitioning species

3.91 score 2 stars 82 scripts 127 downloads 26 exports 15 dependencies

Last updated 7 months agofrom:5e8e4fe774. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 17 2024
R-4.5-win	OK	Dec 17 2024
R-4.5-linux	OK	Dec 17 2024
R-4.4-win	OK	Dec 17 2024
R-4.4-mac	OK	Dec 17 2024
R-4.3-win	OK	Dec 17 2024
R-4.3-mac	OK	Dec 17 2024

Exports:allComb bestmodel bestpart beta2i bsmooth check_strata checkComb col2gray fix_levels getMLE iquantile kComb lcplot lorenz multicut multicut1 occolors oComb ocoptions opticut opticut1 optilevels rankComb strata uncertainty wplot

Dependencies:betareg flexmix Formula lattice lmtest MASS Matrix mefa4 modeltools nnet pbapply pscl ResourceSelection sandwich zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Likelihood Based Optimal Partitioning and Indicator Species Analysis	opticut-package
Finding All Possible Binary Partitions	allComb checkComb kComb
Best model, Partition, and MLE	bestmodel bestpart getMLE
Scaling for the Indicator Potential	beta2i
Bird Species Detections	birdrec
Land Snail Data Set	dolina
Lorenz Curve Based Thresholds and Partitions	iquantile iquantile.lorenz lorenz plot.lorenz print.summary.lorenz quantile.lorenz summary.lorenz
Multi-level Response Model	as.data.frame.multicut as.data.frame.summary.multicut bestmodel.multicut bestpart.multicut fitted.multicut getMLE.multicut lcplot lcplot.multicut1 multicut multicut.default multicut.formula multicut1 plot.multicut plot.multicut1 predict.multicut print.multicut print.multicut1 print.summary.multicut strata.multicut subset.multicut summary.multicut
Color Palettes for the opticut Package	col2gray occolors
Options for the opticut Package	ocoptions
Optimal Binary Response Model	as.data.frame.opticut as.data.frame.summary.opticut bestmodel.opticut bestpart.opticut fitted.opticut fix_levels getMLE.opticut opticut opticut.default opticut.formula opticut1 plot.opticut predict.opticut print.opticut print.opticut1 print.summary.opticut strata strata.opticut subset.opticut summary.opticut wplot wplot.opticut wplot.opticut1
Optimal Number of Factor Levels	bestmodel.optilevels optilevels
Ranking Based Binary Partitions	oComb rankComb
Quantifying Uncertainty for Fitted Objects	as.data.frame.summary.uncertainty as.data.frame.uncertainty bestpart.uncertainty bestpart.uncertainty1 bsmooth bsmooth.uncertainty bsmooth.uncertainty1 check_strata print.summary.uncertainty print.uncertainty print.uncertainty1 strata.uncertainty subset.uncertainty summary.uncertainty uncertainty uncertainty.multicut uncertainty.opticut
Warblers Data Set	warblers