Imports: assertthat, bit64, DBI, curl, glue (>= 1.3.0), httr, jsonlite,
methods, prettyunits, progress, Rcpp, tibble

person("Hadley", "Wickham", , "hadley@rstudio.com", c("aut", "cre"),
person("Jennifer", "Bryan", , "jenny@rstudio.com", "aut",
Imports: assertthat, bit64, curl, DBI, gargle (>= 0.3.0), glue (>=
1.3.0), httr, jsonlite, methods, prettyunits, progress, Rcpp,
Suggests: covr, DBItest, dbplyr, dplyr (>= 0.7.0), hms, readr, sodium,
Collate: 'RcppExports.R' 'bigrquery.R' 'bq-auth.R' 'bq-dataset.R'
Author: Hadley Wickham [aut, cre] (<https://orcid.org/0000-0003-4757-117X>),

Imports: assertthat, bit64, curl, DBI, gargle (>= 0.5.0), glue (>=
Suggests: covr, DBItest, dbplyr (>= 1.3.0), dplyr (>= 0.7.0), hms,
readr, sodium, testthat (>= 2.1.0), withr

Suggests: covr, DBItest, dbplyr (>= 1.3.0), dplyr (>= 0.7.0), blob,
hms, wk (>= 0.3.2), readr, sodium, testthat (>= 2.1.0), withr

person(given = "Kungliga Tekniska Högskolan",
person(given = "The NetBSD Foundation, Inc.",
Imports: assertthat, bit64, curl, DBI, gargle (>= 1.2.0), glue (>=
1.3.0), httr, lifecycle, jsonlite, methods, prettyunits,
progress, Rcpp, rlang (>= 0.4.9), tibble
Suggests: blob, covr, DBItest, dbplyr (>= 1.3.0), dplyr (>= 0.7.0),
hms, readr, sodium, testthat (>= 2.1.0), withr, wk (>= 0.3.2)

person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre"),
person("Jennifer", "Bryan", , "jenny@rstudio.com", role = "aut",
person("Kungliga Tekniska Högskolan", role = "ctb",
person("The NetBSD Foundation, Inc.", role = "ctb",
Imports: assertthat, bit64, brio, curl, DBI, gargle (>= 1.2.0), glue
(>= 1.3.0), httr, jsonlite, lifecycle, methods, prettyunits,
Suggests: blob, covr, DBItest, dbplyr (>= 2.2.1), dplyr (>= 0.7.0),
hms, readr, sodium, testthat (>= 3.0.0), withr, wk (>= 0.3.2)
Packaged: 2022-10-27 22:42:36 UTC; hadleywickham

Title: Fast Generation of High-Dimensional Random Vectors
Description: Simulate multivariate data with arbitrary marginal distributions.
'bigsimr' is an package for simulating high-dimensional multivariate data with a target correlation and arbitrary marginal distributions via Gaussian copula.
It utilizes a Julia package named 'Bigsimr.jl' for its core routines.
SystemRequirements: Julia (>= 1.5), Bigsimr.jl, Distributions.jl