Title: Access Cropland Data Layer Data via the 'CropScape' Web Service
Authors@R: c(person(given = "Bowen", family = "Chen", role = c("aut", "cre"), email = "bwchen0719@gmail.com", comment = c(ORCID = "0000-0003-0370-2756")),
person(given = "Benjamin", family = "Gramig", role = "ctb"))
Description: Interface to easily access Cropland Data Layer (CDL) data for any area of interest via the 'CropScape' <https://nassgeodata.gmu.edu/CropScape/> web service.
Imports: dplyr (>= 0.8.3), magrittr (>= 1.5), raster (>= 3.0), rgdal
Author: Bowen Chen [aut, cre] (<https://orcid.org/0000-0003-0370-2756>),

person(given = "Benjamin", family = "Gramig", role = "ctb"),
person(given = "Taro", family = "Mieno", role = "ctb"))

Title: A Partial Clustering Algorithm with Automatic Estimation of the
Number of Clusters and Identification of Outliers
Description: Computes a partial clustering algorithm that combines
the Ward's minimum variance and Complete Linkage algorithms, providing
automatic estimation of a suitable number of clusters and identification of
Packaged: 2016-03-29 11:08:54 UTC; paola.tellaroli

email = "bazzi [at] stat [dot] unipd [dot] it",
email = "mdonato [at] stanford [dot] edu",
email = "livio [dot] finos [at] unipd [dot] it",
email = "philippe [dot] courcoux [at] oniris-nantes [dot] fr",
email = "corrado [dot] lanera [at] unipd [dot] it",
Description: Provide the CrossClustering algorithm (Tellaroli et al. (2016)
<doi:10.1371/journal.pone.0152333>), which is a partial clustering algorithm
that combines the Ward's minimum variance and Complete Linkage algorithms,
providing automatic estimation of a suitable number of clusters and
Imports: cluster, mclust, flip, magrittr, purrr, utils, assertive,

Title: Cross-Screening in Observational Studies that Test Many
Authors@R: c(person("Paul", "Rosenbaum", email = "rosenbap@wharton.upenn.edu", role = c("aut")),
person("Qingyuan", "Zhao", email = "qyzhao@wharton.upenn.edu", role = c("aut", "cre")))
Description: Cross-screening is a new method that uses both random halves of the sample to screen and test many hypotheses. It generally improves statistical power in observational studies when many hypotheses are tested simultaneously.
Imports: stats, sensitivitymw, parallel, plyr, tables