The package is originally published as Cotton, R.J., Ploier, B., Goren,
M.A., Menon, A.K., and Graumann, J. (2017). flippant–An R package for the
automated analysis of fluorescence-based scramblase assays. BMC
"johannes.graumann@mpi-bn.mpg.de", role = c("cre", "aut")),
Imports: assertive.base (>= 0.0-7), assertive.files (>= 0.0-2),
assertive.numbers (>= 0.0-2), assertive.properties (>= 0.0-4),
assertive.strings (>= 0.0-3), assertive.types (>= 0.0-3),
data.table (>= 1.11.4), magrittr (>= 1.5), minpack.lm (>=

Title: Flexible Inference via Permutations in R
Description: A flexible permutation framework for hypothesis
testing, ANOVA and regression analysis of complex data.
Suggests: rmarkdown, knitr, covr, tidyverse, plotly, htmlwidgets,

Description: A flexible permutation framework for making
inference such as point estimation, confidence
intervals or hypothesis testing, on any kind of data,
be it univariate, multivariate, or more complex such
as network-valued data, topological data, functional
Imports: purrr, rlang, magrittr, cli, ggplot2, tibble, withr,

viridisLite, Rcpp, R6, pbapply, dials, usethis, optimParallel,

Author: Jesse Hemerik, Jelle Goeman and Livio Finos
Description: Provides two robust tests for testing in GLMs,
The tests are often robust against overdispersion,
Packaged: 2017-12-06 13:30:57 UTC; jbahemerik

Description: Provides robust tests for testing in GLMs,

Title: Robust Score Testing in GLMs, by Sign-Flip Contributions
Author: Livio Finos, Jesse Hemerik and Jelle Goeman with contribution by Vittorio Giatti
Description: Provides robust tests for testing in GLMs, by sign-flipping score contributions. The tests are robust against overdispersion, heteroscedasticity and, in some cases, ignored nuisance variables. See Hemerik, Goeman and Finos (2020) <doi:10.1111/rssb.12369>.

Author: Livio Finos, Jelle Goeman and Jesse Hemerik, with contribution of Riccardo De Santis.

Description: R comes with a suite of utilities for linear algebra with "numeric"
(double precision) vectors/matrices. However, sometimes single precision (or
less!) is more than enough for a particular task.  This package extends R's
linear algebra facilities to include 32-bit float (single precision) data.
Float vectors/matrices have half the precision of their "numeric"-type but
are generally faster to numerically operate on, for a performance vs
accuracy trade-off.  The internal representation is an S4 class, which
allows us to keep the syntax identical to that of base R's.  Interaction
between floats and base types for binary operators is generally possible; in
these cases, type promotion always defaults to the higher precision.  The
package ships with copies of the single precision 'BLAS' and 'LAPACK', which
are automatically built in the event they are not available on the system.
Copyright: The copyright for the single precision BLAS/LAPACK
distribution located in src/lapack is given in the file
person("Drew", "Schmidt", role=c("aut", "cre", "cph"), email="wrathematics@gmail.com"),
person("Wei-Chen", "Chen", role="ctb", comment="win32 fixes"),