Description: This implements the data table back-end for 'dplyr' so that you
can seamlessly use data table and 'dplyr' together.
Imports: dplyr (>= 0.5.0), data.table, lazyeval
Suggests: Lahman, nycflights13, testthat, covr

person("Lionel", "Henry", , "lionel@rstudio.com", role = "cre"),
person("Hadley", "Wickham", , "hadley@rstudio.com", role = "aut"),

Imports: dplyr (>= 0.5.0), data.table (>= 1.9.6), lazyeval, rlang

Description: Provides a data.table backend for 'dplyr'. The goal of 'dtplyr'
is to allow you to write 'dplyr' code that is automatically translated to
the equivalent, but usually much faster, data.table code.
Imports: crayon, data.table (>= 1.9.6), dplyr (>= 0.8.1), rlang,
Suggests: bench, covr, knitr, rmarkdown, testthat (>= 2.1.0)

Imports: crayon, data.table (>= 1.12.4), dplyr (>= 0.8.1), rlang,

Description: Provides a data.table backend for 'dplyr'. The goal
of 'dtplyr' is to allow you to write 'dplyr' code that is
automatically translated to the equivalent, but usually much faster,
Imports: crayon, data.table (>= 1.12.4), dplyr (>= 1.0.3), ellipsis,
glue, lifecycle, rlang, tibble, tidyselect, vctrs
Suggests: bench, covr, knitr, rmarkdown, testthat (>= 3.0.0), tidyr (>=

Imports: crayon, data.table (>= 1.13.0), dplyr (>= 1.0.3), ellipsis,
Packaged: 2021-12-03 16:20:10 UTC; hadleywickham

person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("cre", "aut")),
person("Mark", "Fairbanks", role = "aut"),
person("Ryan", "Dickerson", role = "aut"),
Description: Provides a data.table backend for 'dplyr'. The goal of
'dtplyr' is to allow you to write 'dplyr' code that is automatically
translated to the equivalent, but usually much faster, data.table
Packaged: 2022-01-19 21:59:49 UTC; hadleywickham

Packaged: 2022-08-20 12:54:11 UTC; hadleywickham

Title: Dynamic Treatment Regimes for Survival Analysis
Author: Shannon T. Holloway, Hunyong Cho
Description: Provides methods for estimating multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring.

Description: Provides methods for estimating multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring. Cho, H., Holloway, S. T., and Kosorok, M. R. (2020) <arXiv:2012.03294>.