concaveman, cvAUC, doFuture, doRNG, fields, foreach, future,
graphics, grDevices, iterators, pls, raster, rgeos, ROCR, sp,
sparr, spatstat.geom, spatstat.random, stats

concaveman, cvAUC, doFuture, doRNG, fields, foreach, future,
graphics, grDevices, iterators, methods, pls, raster, rgeos,
ROCR, sp, sparr, spatstat.geom, stats
R.rsp, spatstat.data, spatstat.random, spelling, testthat,
utils

c(person(given = "Ian D.",
family = "Buller",
role = c("aut", "cre", "cph"),
email = "ian.buller@alumni.emory.edu",
comment = c(ORCID = "0000-0001-9477-8582")),
person(given = "Lance A.",
family = "Waller",
role = c("ctb", "ths"),
email = "lwaller@emory.edu",
comment = c(ORCID = "0000-0001-5002-8886")),
person(given = "Emory University",
role = "cph"))
Estimates an ecological niche using occurrence data, covariates, and kernel
density-based estimation methods. For a single species with presence and absence data,
the 'envi' package uses the spatial relative risk function that is estimated using the
'sparr' package. Details about the 'sparr' package methods can be found in the tutorial:
Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can
be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about
relative risk functions using kernel density estimation can be found in J. F. Bithell
(1991) <doi:10.1002/sim.4780101112>.
concaveman, cvAUC, doFuture, doRNG, fields, foreach, future,
graphics, grDevices, iterators, pls, raster, rgeos, ROCR, sp,
sparr, spatstat.geom, stats
maptools, R.rsp, RStoolbox, spatstat.data, spatstat.random,
spelling, testthat, utils

concaveman, cvAUC, doParallel, fields, foreach, graphics,
grDevices, maptools, parallel, pls, raster, rgeos, ROCR, sp,
sparr, spatstat, stats, utils

concaveman, cvAUC, doParallel, fields, foreach, graphics,
grDevices, maptools, parallel, pls, raster, rgeos, ROCR, sp,
sparr, spatstat.geom, spatstat.core, stats, utils

GC-MS Data Analysis for Environmental Science
person("Miao","YU", email =
"yufreecas@gmail.com", role = c("aut", "cre"))
Gas Chromatography-Mass Spectrometer(GC-MS) Data Analysis for Environmental Science. This package covered topics such as raw data process, molecular isotope ratio, matrix effects, etc. in environmental analysis.