Package: hypervolume 3.1.4
hypervolume: High Dimensional Geometry, Set Operations, Projection, and Inference Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls
Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
Authors:
hypervolume_3.1.4.tar.gz
hypervolume_3.1.4.tar.gz(r-4.5-noble)hypervolume_3.1.4.tar.gz(r-4.4-noble)
hypervolume_3.1.4.tgz(r-4.4-emscripten)hypervolume_3.1.4.tgz(r-4.3-emscripten)
hypervolume.pdf |hypervolume.html✨
hypervolume/json (API)
# Install 'hypervolume' in R: |
install.packages('hypervolume', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bblonder/hypervolume/issues
- acacia_pinus - Data for Acacia and Pinus tree distributions
- circles - Circles simulated dataset
- morphSnodgrassHeller - Morphological data for Darwin's finches
- quercus - Data and demo for Quercus (oak) tree distributions
Last updated 8 months agofrom:e88cf660cb. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 28 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 28 2024 |
Exports:copy_param_hypervolumeestimate_bandwidthexpectation_ballexpectation_boxexpectation_convexexpectation_maximalfind_optimal_occupancy_thinget_centroidget_centroid_weightedget_occupancy_intersection_bootstrapget_occupancy_statsget_occupancy_stats_bootstrapget_occupancy_unshared_bootstrapget_occupancy_volume_bootstrapget_relative_volumeget_volumehypervolumehypervolume_boxhypervolume_distancehypervolume_estimate_probabilityhypervolume_funnelhypervolume_gaussianhypervolume_general_modelhypervolume_holeshypervolume_inclusion_testhypervolume_joinhypervolume_n_occupancyhypervolume_n_occupancy_bootstraphypervolume_n_occupancy_permutehypervolume_n_occupancy_testhypervolume_n_resamplehypervolume_overlap_confidencehypervolume_overlap_statisticshypervolume_overlap_testhypervolume_permutehypervolume_projecthypervolume_prunehypervolume_redundancyhypervolume_resamplehypervolume_save_animated_gifhypervolume_segmenthypervolume_sethypervolume_set_n_intersectionhypervolume_svmhypervolume_thinhypervolume_thresholdhypervolume_to_data_framehypervolume_variable_importanceoccupancy_bootstrap_gofoccupancy_filteroccupancy_to_intersectionoccupancy_to_unionoccupancy_to_unsharedpadded_rangeplot.Hypervolumeplot.HypervolumeListprint.Hypervolumeprint.HypervolumeListshow.Hypervolumeshow.HypervolumeListsummary.Hypervolumesummary.HypervolumeListto_hv_listweight_data
Dependencies:abindcaretclasscliclockcodetoolscolorspacecpp11crayondata.tablediagramdigestdoParalleldplyre1071fansifarverfastclusterFNNforeachfuturefuture.applygenericsgeometryggplot2globalsgluegowergtablehardhathitandrunhmsipredisobanditeratorskernlabKernSmoothkslabelinglatticelavalifecyclelinproglistenvlpSolvelubridatemagicmagrittrmapsMASSMatrixmclustmgcvModelMetricsmulticoolmunsellmvtnormnlmennetnumDerivpalmerpenguinsparallellypbapplypdistpillarpkgconfigplyrpracmaprettyunitspROCprodlimprogressprogressrproxypurrrR6rasterrcddRColorBrewerRcppRcppArmadilloRcppProgressrecipesreshape2rlangrpartscalesshapespSQUAREMstringistringrsurvivalterratibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr