c(
person("Xiaodong","Song",role = c("aut"),email = "xdsong@issas.ac.cn"),
person("Gaoqiang","Ge",role = c("aut","cre"),email = "gaoqiangge2020@163.com"),
person("Jun","Zhu",role = c("aut")),
person("Ganlin","Zhang",role = c("aut"))
)
methods, pryr, utils, caret, geoR, gstat, quantregForest,
randomForest, rgdal, stats, sp,
Xiaodong Song [aut],
Gaoqiang Ge [aut, cre],
Jun Zhu [aut],
Ganlin Zhang [aut]

methods, pryr, utils, caret, geoR, gstat, quantregForest,
randomForest, stringr, rgdal, stats,

c(
person("Xiaodong","Song",role = c("aut"),email = "xdsong@issas.ac.cn"),
person("Peicong","Tang",role=c("aut","cre"),email = "peicongtang0409@163.com"),
person("Gaoqiang","Ge",role = c("aut"),email = "gaoqiangge2020@163.com"),
person("Jun","Zhu",role = c("aut")),
person("Ganlin","Zhang",role = c("aut"))
)
Parallel computing, multi-core CPU is used to efficiently compute
and process multi-dimensional soil data.This package includes the
parallelized 'Quantile Regression Forests' algorithm for Digital Soil Mapping
and is mainly dependent on the package 'quantregForest' and 'snowfall'.
Detailed references to the R package and the web site are described in the
methods, as detailed in the method documentation.
methods, pryr, utils, caret, gstat, quantregForest,
randomForest, stringr, rgdal, stats,
Xiaodong Song [aut],
Peicong Tang [aut, cre],
Gaoqiang Ge [aut],
Jun Zhu [aut],
Ganlin Zhang [aut]

c(
person("Xiaodong","Song",role = c("aut"),email = "xdsong@issas.ac.cn"),
person("Peicong","Tang",role=c("aut","cre"),email = "peicongtang0409@163.com"),
person("Wentao", "Zhu", role=c("aut"), email = "1306395569@qq.com"),
person("Gaoqiang","Ge",role = c("aut"),email = "gaoqiangge2020@163.com"),
person("Jun","Zhu",role = c("aut")),
person("Ganlin","Zhang",role = c("aut"))
)
Xiaodong Song [aut],
Peicong Tang [aut, cre],
Wentao Zhu [aut],
Gaoqiang Ge [aut],
Jun Zhu [aut],
Ganlin Zhang [aut]

Random Forest Classification with Parallel Computing
R package implementing random forest classification using parallel computing, built with Fortran and OpenMP in the backend.