Matrix (>= 1.2.3), parallel, magrittr, MASS, methods

Parametric Bootstrap, Kenward-Roger and Satterthwaite Based
Methods for Test in Mixed Models
c(
person(given = "Ulrich", family = "Halekoh",
email = "uhalekoh@health.sdu.dk", role = c("aut", "cph")),
person(given = "Søren", family = "Højsgaard",
email = "sorenh@math.aau.dk", role = c("aut", "cre", "cph"))
)
Test in mixed effects models. Attention is on mixed
effects models as implemented in the 'lme4' package. For linear
mixed models, this package implements (1) a parametric bootstrap
test, (2) a Kenward-Roger-typ modification of F-tests for linear
mixed effects models and (3) a Satterthwaite-type modification of
F-tests for linear mixed effects models. The package also
implements a parametric bootstrap test for generalized linear
mixed models.  The facilities of the package are documented in the
paper by Halehoh and Højsgaard, (2012,
<doi:10.18637/jss.v059.i09>).  Please see 'citation("pbkrtest")'
for citation details.
broom, dplyr, magrittr, MASS, Matrix (>= 1.2.3), methods,
numDeriv, parallel, knitr
Ulrich Halekoh [aut, cph],
Søren Højsgaard [aut, cre, cph]

person("Jonathan", "Davies", email = "jd769@bath.ac.uk", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4986-8594"))
Binding models which are useful when analysing protein-ligand interactions by techniques such as Biolayer Interferometry (BLI) or Surface Plasmon Resonance (SPR). Naman B. Shah, Thomas M. Duncan (2014) <doi:10.3791/51383>. Hoang H. Nguyen et al. (2015) <doi:10.3390/s150510481>. After initial binding parameters are known, binding curves can be simulated and parameters can be varied. The models within this package may also be used to fit a curve to measured binding data using non-linear regression.
Jonathan Davies [aut, cre] (<https://orcid.org/0000-0002-4986-8594>)

person("Jonathan", "Davies", email = "jonathanrd@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4986-8594"))
testthat, knitr, rmarkdown, ggplot2, gridExtra

Tracking the Progress of Mc*pply with Progress Bar
A light-weight package helps you track and visualize
the progress of parallel version of vectorized R functions (mc*apply).