mvtnorm, multcomp, mratios, graphics, stats

Simultaneous tests and confidence intervals are provided for one-way experimental designs with one or many normally distributed, primary response variables (endpoints). Differences (Hasler and Hothorn, 2011 <doi:10.2202/1557-4679.1258>) or ratios (Hasler and Hothorn, 2012 <doi:10.1080/19466315.2011.633868>) of means can be considered. Various contrasts can be chosen, unbalanced sample sizes are allowed as well as heterogeneous variances (Hasler and Hothorn, 2008 <doi:10.1002/bimj.200710466>) or covariance matrices (Hasler, 2014 <doi:10.1515/ijb-2012-0015>).

c(person(c("Berwin", "A."), "Turlach",
role=c("aut", "cre"),
email="Berwin.Turlach@gmail.com"),
person("Nader", "Tajvidi", role="ctb",
email="Nader.Tajvidi@matstat.lu.se"))
Provides a framework to generating random variates from
arbitrary multivariate copulae, while concentrating on
(bivariate) extreme value copulae.  Particularly useful if
the multivariate copulae are not available in closed
form.
Berwin A. Turlach [aut, cre],
Nader Tajvidi [ctb]

This package simulates correlated multinomial responses
utilizing threshold approaches and assuming a cumulative link
model or a baseline category logit model for the univariate
marginal probabilities.

Simulates correlated multinomial responses by utilizing
threshold approaches under a marginal cumulative link model, a
marginal continuation ratio model or a marginal baseline
category logit model.

Simulates correlated multinomial responses by utilizing threshold approaches under a cumulative link model, a continuation ratio model or a baseline category logit marginal model specification.

Simulates correlated multinomial responses by utilizing threshold approaches under a cumulative link model, a continuation ratio model or a baseline-category logit marginal model specification.

Simulates correlated multinomial responses by utilizing threshold
approaches under a marginal model specification.

Simulates correlated multinomial responses conditional on a marginal model specification.
c(person("Anestis", "Touloumis", role = c("aut", "cre"), email = "A.Touloumis@brighton.ac.uk"))