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enmSdmX
View on CRAN: Click
here
Download and install enmSdmX package within the R console
Install from CRAN:
install.packages("enmSdmX")
Install from Github:
library("remotes")
install_github("cran/enmSdmX")
Install by package version:
library("remotes")
install_version("enmSdmX", "1.2.12")
Attach the package and use:
library("enmSdmX")
Maintained by
Adam B. Smith
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.enmSdmX . https://github.com/adamlilith/enmSdmX/issues . https://github.com/adamlilith/enmSdmX . enmSdmX citation info . enmSdmX results . enmSdmX.pdf . enmSdmX_1.2.12.tar.gz . enmSdmX_1.2.12.zip . enmSdmX_1.2.12.zip . enmSdmX_1.2.12.zip . enmSdmX_1.2.12.tgz . enmSdmX_1.2.12.tgz . enmSdmX_1.2.12.tgz . enmSdmX_1.2.12.tgz . enmSdmX archive . https://CRAN.R-project.org/package=enmSdmX .
First Published: 2022-12-12
Latest Update: 2023-09-08
Description:
Implements species distribution modeling and ecological niche
modeling, including: bias correction, spatial cross-validation, model
evaluation, raster interpolation, biotic "velocity" (speed and
direction of movement of a "mass" represented by a raster), interpolating
across a time series of rasters, and use of spatially imprecise records.
The heart of the package is a set of "training" functions which
automatically optimize model complexity based number of available
occurrences. These algorithms include MaxEnt, MaxNet, boosted regression
trees/gradient boosting machines, generalized additive models,
generalized linear models, natural splines, and random forests. To enhance
interoperability with other modeling packages, no new classes are created.
The package works with 'PROJ6' geodetic objects and coordinate reference
systems.
How to cite:
Adam B. Smith (2022). enmSdmX: Species Distribution Modeling and Ecological Niche Modeling. R package version 1.2.12, https://cran.r-project.org/web/packages/enmSdmX. Accessed 12 May. 2025.
Previous versions and publish date:
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Other R packages that enmSdmX depends,
imports, suggests or enhances
Complete documentation for enmSdmX
Functions, R codes and Examples using
the enmSdmX R package
Some associated functions: bioticVelocity . compareResponse . coordImprecision . countPoints . crss . customAlbers . decimalToDms . dmsToDecimal . dot-calcWeights . dot-cardinalDistance . dot-euclid . dot-interpCoordFromQuantile . dot-scalePredictors . elimCellDuplicates . enmSdmX . evalAUC . evalContBoyce . evalMultiAUC . evalTSS . evalThreshold . evalThresholdStats . evalTjursR2 . extentToVect . geoFold . geoFoldContrast . geoThin . getCRS . getValueByCell . globalx . interpolateRasts . lemurs . longLatRasts . mad0 . mad1 . madClim . madClim2030 . madClim2050 . madClim2070 . madClim2090 . modelSize . nearestEnvPoints . nearestGeogPoints . nicheOverlapMetrics . plotExtent . predictEnmSdm . predictMaxEnt . predictMaxNet . sampleRast . spatVectorToSpatial . squareCellRast . summaryByCrossValid . trainBRT . trainByCrossValid . trainGAM . trainGLM . trainMaxEnt . trainMaxNet . trainNS . trainRF . troubleshooting_parallel_operations . weightByDist .
Some associated R codes: Full enmSdmX package functions and examples
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