Tools to Support the Sheffield Elicitation Framework

ggplot2, grid, shiny, stats, graphics, tidyr, MASS, ggExtra,
gridExtra, scales, rmarkdown, grDevices

Implements various methods for eliciting a probability distribution
for a single parameter from an expert or a group of experts. The expert
provides a small number of probability judgements, corresponding
to points on his or her cumulative distribution function. A range of parametric
distributions can then be fitted and displayed, with feedback provided in the
form of fitted probabilities and percentiles. For multiple experts, a weighted
linear pool can be calculated. Also includes functions for eliciting beliefs
about population distributions, eliciting multivariate distributions using a
Gaussian copula, eliciting a Dirichlet distribution, and eliciting distributions
for variance parameters in a random effects meta-analysis model. R Shiny apps
for most of the methods are included.
ggplot2, grid, shiny, stats, graphics, tidyr, MASS, ggExtra,
gridExtra, scales, rmarkdown, grDevices, shinyMatrix, utils

ggplot2, grid, shiny, stats, graphics, tidyr, MASS, ggExtra,
gridExtra, scales, rmarkdown, grDevices, shinyMatrix, utils,
ggridges, Hmisc

SHrinkage covariance Incorporating Prior knowledge
The SHIP-package allows the estimation of various types of
shrinkage covariance matrices. These types differ in terms of
the so-called covariance target (to be chosen by the user), the
highly structured matrix which the standard unbiased sample
covariance matrix is shrunken towards and which optionally
incorporates prior biological knowledge extracted from the
database KEGG. The shrinkage intensity is obtained via an
analytical procedure.

A statistical method designed to take advantage of population genetics and microevolutionary theory, specifically by testing the association between haplotype sharing length and trait of interest.
stringr, geepack, Matrix, FactoMineR, kinship2, foreach, MASS,
doParallel

c(person("Kyoungjae","Lee",role="aut",email="leekjstat@gmail.com"),person("Lizhen", "Lin", role = "aut", email="lizhen.lin@nd.edu"),person("Hyungmin", "Park", role = "aut", email="hmpark0702@korea.ac.kr"),person("Kisung", "You", role = c("aut", "cre"),email = "ksyou496@gmail.com",comment=c(ORCID="0000-0002-8584-459X")))
We provide a collection of statistical hypothesis testing procedures ranging from classical to modern methods for non-trivial settings such as high-dimensional scenario. For the general treatment of statistical hypothesis testing, see the book by Lehmann and Romano (2005) <doi:10.1007/0-387-27605-X>.
Rcpp, Rdpack, stats, utils, fastclime, pracma
Kyoungjae Lee [aut],
Lizhen Lin [aut],
Hyungmin Park [aut],
Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)