adapt -- multidimensional numerical integration
adapt
1.0
FORTRAN by Alan Genz, S by Mike Meyer, R by Thomas Lumley and Martin Maechler
Adaptive Quadrature in up to 20 dimensions
Unclear (Fortran) -- code in Statlib's ./S/adapt
Thomas Lumley <tlumley@u.washington.edu>

Adaptive Approaches for Signal Detection in Pharmacovigilance
c(person("Emeline", "Courtois", email = "emeline.courtois@inserm.fr", role = c("cre")),
person("Ismaïl", "Ahmed", email = "ismail.ahmed@inserm.fr", role = c("aut")),
person("Hervé", "Perdry", email = "herve.perdry@universite-paris-saclay.fr", role = c("ctb")))
A collection of several pharmacovigilance signal detection methods based on adaptive lasso. Additional lasso-based and propensity score-based signal detection approaches are also supplied.
Emeline Courtois [cre],
Ismaïl Ahmed [aut],
Hervé Perdry [ctb]

A collection of several pharmacovigilance signal detection methods based on adaptive lasso. Additional lasso-based and propensity score-based signal detection approaches are also supplied. See Courtois et al <doi:10.1186/s12874-021-01450-3>.

The adaptive mixture discriminant analysis (AMDA) allows to adapt a model-based classifier to the situation where a class represented in the test set may have not been encountered earlier in the learning phase.

Bayesian Adaptive Designs for Diagnostic Trials
c(
person("Graeme L.", "Hickey",
email = "graemeleehickey@gmail.com",
role = c("cre", "aut")),
person("Yongqiang", "Zhang",
email = "yongqiang.zhang@bd.com",
role = "aut"),
person(given = "Becton, Dickinson and Company",
role = "cph")
)
Simulate clinical trials for diagnostic test devices and evaluate
the operating characteristics under an adaptive design with futility
assessment determined via the posterior predictive probabilities.
doParallel, extraDistr, foreach, parallel, pbmcapply, stats
rmarkdown, knitr, testthat (>= 3.0.0), VGAM, covr
Graeme L. Hickey [cre, aut],
Yongqiang Zhang [aut],
Becton, Dickinson and Company [cph]

Adaptive Bioequivalence Design for In-Vitro Permeation Tests
c(
person("Daeyoung", "Lim", email = "daeyoung.lim@uconn.edu",
role = c("aut", "cre")),
person("Elena", "Rantou", email = "Elena.Rantou@fda.hhs.gov", role = "ctb"),
person("Jessica", "Kim", email = "Jessica.Kim@fda.hhs.gov", role = "ctb"),
person("Sungwoo", "Choi", email = "Sungwoo.Choi@fda.hhs.gov", role = "ctb"),
person("Nam Hee", "Choi", email = "NamHee.Choi@fda.hhs.gov", role = "ctb"),
person("Stella", "Grosser", email = "Stella.Grosser@fda.hhs.gov", role = "ctb"))
Contains functions carrying out adaptive procedures using mixed scaling approach to establish bioequivalence for in-vitro permeation test (IVPT) data. Currently, the package provides procedures based on parallel replicate design and balanced data, according to the U.S. Food and Drug Administration's "Draft Guidance on Acyclovir" <https:www.accessdata.fda.gov/drugsatfda_docs/psg/Acyclovir_topical cream_RLD 21478_RV12-16.pdf>. Potvin et al. (2008) <doi:10.1002/pst.294> provides the basis for our adaptive design (see Method B). This package reflects the views of the authors and should not be construed to represent the views or policies of the U.S. Food and Drug Administration.
Daeyoung Lim [aut, cre],
Elena Rantou [ctb],
Jessica Kim [ctb],
Sungwoo Choi [ctb],
Nam Hee Choi [ctb],
Stella Grosser [ctb]