person("Matthew", "Strimas-Mackey", email = "mes335@cornell.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8929-7776")),
Imports: assertthat, countrycode (>= 1.0.0), dplyr (>= 0.7.0), rlang,
Suggests: covr, data.table, knitr, readr, rmarkdown, testthat
Author: Matthew Strimas-Mackey [aut, cre]

Title: eBird Data Extraction and Processing in R
Suggests: covr, data.table, knitr, readr, rmarkdown, testthat, unmarked

Imports: assertthat, countrycode (>= 1.0.0), dplyr (>= 0.7.8), rlang
(>= 0.3.0), stringi, stringr, tidyr (>= 0.8.0), utils, httr

person(given = "Cornell Lab of Ornithology",
Description: Extract and process bird sightings records from
eBird (<http://ebird.org>), an online tool for recording bird
observations.  Public access to the full eBird database is via the
eBird Basic Dataset (EBD; see <http://ebird.org/ebird/data/download>
for access), a downloadable text file. This package is an interface to
AWK for extracting data from the EBD based on taxonomic, spatial, or
temporal filters, to produce a manageable file size that can be
Imports: assertthat, countrycode (>= 1.0.0), dplyr (>= 0.7.8), httr,
magrittr, rlang (>= 0.3.0), stringi, stringr, tidyr (>= 0.8.0),

Suggests: covr, data.table, knitr, readr, rmarkdown, sf, testthat,

magrittr, readr (>= 2.0.0), rlang (>= 0.3.0), stringi, stringr,
Suggests: covr, knitr, rmarkdown, sf, testthat, unmarked

Title: Area Under Minimum of False Positives and Negatives
Description: Standard template library sort is
algorithm <arXiv:2107.01285> for computing Area Under Minimum and
Suggests: testthat, ggplot2, WeightedROC, penaltyLearning, knitr,
markdown, mlbench, directlabels, microbenchmark, covr

Title: Generates PFA Documents from R Code and Optionally Runs Them
Description: Provides tools for converting R objects and syntax into the Portable
Format for Analytics (PFA). Allows for testing validity and runtime behavior
of PFA documents through rPython and Titus, a more complete implementation of
PFA for Python. The Portable Format for Analytics is a specification for
event-based processors that perform predictive or analytic calculations and is aimed
at helping smooth the transition from statistical model development to large-scale
and/or online production. See <http://dmg.org/pfa> for more information.
person("Steven", "Mortimer", , "reportmort@gmail.com", c("aut", "cre")),
person("Collin", "Bennett", , "collin.bennett@opendatagroup.com", c("aut")),
Imports: methods, stats, utils, jsonlite (>= 1.1), gbm (>= 2.1.1),
Suggests: knitr, rmarkdown, testthat, MASS, forecast, caret, ipred,
Collate: 'arima.R' 'aurelius.R' 'avro.R' 'avro_from_df.R'
'ets.R' 'forecast.R' 'gbm.R' 'gen_unique_name.R' 'glm.R'
'glmnet.R' 'holtwinters.R' 'jsonobj.R' 'kcca.R' 'kmeans.R'
'knn.R' 'lda.R' 'lm.R' 'naiveBayes.R' 'pfa.R' 'pfa_cellpool.R'
'randomForest.R' 'read_pfa.R' 'rpart.R' 'write_pfa.R' 'zzz.R'
Packaged: 2017-07-03 00:27:47 UTC; steven.mortimer