Title: Bayesian Inference for A|B and Bandit Marketing Tests
Description: Uses simple Bayesian conjugate prior update rules to calculate
the win probability of each option, value remaining in the test, and
percent lift over the baseline for various marketing objectives.
Fink, Daniel (1997) "A Compendium of Conjugate Priors" <doi:10.1.1.157/5540>.
Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <http://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.
Imports: purrr, dplyr, tidyr, magrittr, tibble, rlang
Suggests: spelling, knitr, testthat (>= 2.1.0), rmarkdown

Fink, Daniel (1997) "A Compendium of Conjugate Priors" <https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>.

Imports: purrr, dplyr, tidyr (>= 1.0.0), magrittr, tibble, rlang

Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <https://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.

Title: Genetic-Relationship-Matrix Structural Equation Modelling
person("Beate", "StPourcain", email = "Beate.StPourcain@mpi.nl", comment = c(ORCID = "0000-0002-4680-3517"), role = c("aut", "cre")),
person("Alexander", "Klassmann", email = "alex.klassmann@koeln.de", role = c("ctb"))
Description: Quantitative genetics tool supporting the modelling of multivariate
genetic variance structures in quantitative data. It allows fitting different
models through multivariate genetic-relationship-matrix (GRM)
structural equation modelling (SEM) in unrelated individuals,
using a maximum likelihood approach. Specifically,
it combines genome-wide genotyping information, as captured by GRMs,
Imports: msm (>= 1.6), numDeriv, optimParallel, stats, utils
Author: Beate StPourcain [aut, cre] (<https://orcid.org/0000-0002-4680-3517>),

Title: General regression neural network
Description: The program GRNN implements the algorithm proposed by
Collate: 'create.R' 'grnn-package.r' 'guess.r' 'kernel.R' 'learn.R'

Title: A Generalized Regression Neural Network
Description: grnnR synthesizes a generalized regression neural network
from the supplied training data, P(atterns) and T(argets)
Packaged: Sun Dec 18 21:48:14 2005; root