Additive partially linear models for differential gene
expression analysis
R (>= 2.14.2), MASS, splines, limma, R.oo
A set of tools for identifying genes whose differential
expression is associated with measurements of other covariates
on a continuous scale.  These methods rely on generalized
additive partially linear models which can be fitted
efficiently using a B-spline basis approximation.  Still under
development: methods for interfacing with objects extending the
eSet class and a function to pass linear models in edgeR and
DEseq format.

This package fits the partially linear mixed effects model
(semiparametric random intercept model) using kernel
regression, without distributional assumptions for the random
terms. Estimation procedure is an iterative generalized least
squares type. A nonparametric heteroskedastic variance function
is allowed for the regression error. Bootstrap resampling is
provided for inference. The package implements bandwidth
selection by an alternative cross validation for correlated
data.

Polytomous logit-normit (graded logistic) model estimation
Performs bivariate composite likelihood and full
information maximum likelihood estimation for polytomous
logit-normit (graded logistic) item response theory (IRT)
models.

Polytomous Logit-Normit (Graded Logistic) Model Estimation

A system to plan analyses within the mental model
where you have one (or more) datasets and want to run either A) the same
function multiple times with different arguments, or B) multiple functions.
This is appropriate when you have multiple strata (e.g. locations, age groups)
that you want to apply the same function to, or you have multiple variables
(e.g. exposures) that you want to apply the same statistical method to, or
when you are creating the output for a report and you need multiple different
tables or graphs.
data.table, R6, uuid, foreach, fs, glue, usethis, purrr,
utils, digest, stats
testthat, knitr, rmarkdown, progressr, ggplot2, readxl,
magrittr

c(
person("Kirill", "Müller", role = c("aut", "cre"), email = "krlmlr+r@mailbox.org"),
person("Sergey", "Podobry", role = "cph", comment = "Author of the bundled plog library"))
A simple header-only logging library for C++.
Add 'LinkingTo: plogr' to 'DESCRIPTION', and '#include <plogr.h>' in your C++ modules to use it.
Kirill Müller [aut, cre],
Sergey Podobry [cph] (Author of the bundled plog library)