Brier score decomposition of probabilistic forecasts for binary
events

Decomposes the empirical Brier score into reliability,
resolution and uncertainty. Two different estimators for the
components are provided: The original estimators proposed by
Murphy (1974), and the bias-corrected estimators proposed by
Ferro and Fricker (2012). Variances of all the components are
estimated. This package applies only to probabilistic
predictions of binary events.

Decomposes the empirical Brier score into reliability, resolution and uncertainty. Two different estimators for the components are provided: The original estimators proposed by Murphy (1974), and the bias-corrected estimators proposed by Ferro and Fricker (2012). Sampling variances of all the components are estimated. This package applies only to probabilistic predictions of binary events.

An Implementation of the Bridge Distribution with Logit-Link as
in Wang and Louis (2003)
person("Bruce", "Swihart", email = "bruce.swihart@gmail.com", role = c("aut", "cre"))
An implementation of the bridge distribution with logit-link in
R. In Wang and Louis (2003) <DOI:10.1093/biomet/90.4.765>, such a univariate
bridge distribution was derived as the distribution of the random intercept that
'bridged' a marginal logistic regression and a conditional logistic regression.
The conditional and marginal regression coefficients are a scalar multiple
of each other. Such is not the case if the random intercept distribution was
Gaussian.
knitr, rmarkdown, reshape2, ggplot2, testthat

Bridge Hand Generator with Criteria Selector
c(person("Jason", "Kaplan", role = c("aut", "cre"),
email = "scjase@gmail.com"))
Produce bridge hands, allowing parameters for hands to offer specific for bidding sequences.
cowplot, dplyr, patchwork, tibble, tidyr, magrittr, ggplot2,
ggedit, glue, gridExtra, kableExtra, pdftools, scales, stringr
LaTeX(texi2dvi) must be present in the system to
create PDF reports

Genome-Wide RNA Degradation Analysis Using BRIC-Seq Data
person("Naoto", "Imamachi", email = "naoto.imamachi@gmail.com", role = c("aut", "cre"))
BRIC-seq is a genome-wide approach for determining RNA stability in mammalian cells.
This package provides a series of functions for performing quality check of your BRIC-seq data,
calculation of RNA half-life for each transcript and comparison of RNA half-lives between two conditions.
data.table, ggplot2, shiny, shinydashboard, plotly, BSDA,
outliers