Presents an explanatory animation of normal quantile-quantile plots based on a water-filling analogy.  The animation presents a normal QQ plot as the parametric plot of the water levels in vases defined by two distributions.  The distributions decorate the axes in the normal QQ plot and are optionally shown as vases adjacent to the plot.  The package draws QQ plots for several distributions, either as samples or continuous functions.

Quantile Regression for Linear Mixed-Effects Models
matrixcalc, mvtnorm, ghyp, quantreg, psych, tcltk
Quantile regression (QR) for Linear
Mixed-Effects Models via the asymmetric Laplace distribution (ALD).
It uses the Stochastic Approximation of the EM (SAEM) algorithm for
deriving exact maximum likelihood estimates and full inference results
for the fixed-effects and variance components.
It also provides graphical summaries for assessing the algorithm
convergence and fitting results.

matrixcalc, mvtnorm, ghyp, quantreg, psych, tcltk, ald

mvtnorm, lqr, quantreg, psych, tcltk, ald

Quantile Regression for Nonlinear Mixed-Effects Models
Quantile regression (QR) for Nonlinear
Mixed-Effects Models via the asymmetric Laplace distribution (ALD).
It uses the Stochastic Approximation of the EM (SAEM) algorithm for
deriving exact maximum likelihood estimates and full inference results
for the fixed-effects and variance components.
It also provides graphical summaries for assessing the algorithm
convergence and fitting results.

Christian E. Galarza <chedgala@espol.edu.ec> and Victor H. Lachos <hlachos@uconn.edu>
mvtnorm, lqr, quantreg, psych, ald, progress
Quantile regression (QR) for Nonlinear
Mixed-Effects Models via the asymmetric Laplace distribution (ALD).
It uses the Stochastic Approximation of the EM (SAEM) algorithm for
deriving exact maximum likelihood estimates and full inference results
for the fixed-effects and variance components.
It also provides prediction and graphical summaries for assessing the algorithm
convergence and fitting results.

Quantal Response Analysis for Dose-Mortality Data
Functions are provided that implement the
use of the Fieller's formula methodology, for
calculating a confidence interval for a ratio of
(possibly, correlated) means.  See Fieller (1954)
<doi:10.1111/j.2517-6161.1954.tb00159.x>.  Here,
the application of primary interest is to studies
of insect mortality response to increasing doses
of a fumigant, or, e.g., to time in coolstorage.
The formula is used to calculate a confidence
interval for the dose or time required to achieve
a specified mortality proportion, commonly 0.5
or 0.99.  A vignette demonstrates link functions
that may be considered, and alternative choices of
error family.  Note in particular the beta-binomial
error family.  See also Maindonald, Waddell,
and Petry (2001) <doi:10.1016/S0925-5214(01)00082-5>.
knitr, rmarkdown, plyr, robustlmm, MASS, fitODBOD, glmmTMB,
VGAM, bbmle, epiphy, latticeExtra, xtable, testDriveR, gamlss,
bookdown, prettydoc, DHARMa, kableExtra, magrittr, afex,
plotrix, dfoptim, optimx