Extension of testthat package to make unit tests on empirical distributions of estimators and functions for diagnostics of their finite-sample performance.

This package provides functions for the implementation of a density goodness-of-fit test, based on piecewise approximation of the L2 distance.

The iterative Bayesian Model Averaging (BMA) algorithm for survival analysis is a variable selection method for applying survival analysis to microarray data.

The ratelimiter module ensures that an operation will not be executed more than a given number of times during a given period.

The Negative Binomial regression with mean and shape modeling and mean and variance modeling and Beta Binomial regression with mean and dispersion modeling.

This experimental data package contains 11 data sets necessary to follow the "TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages".

Random shuffle implementation, on immutable lists. Based on perfect shuffle implementation by Oleg Kiselyov.

Test::Requires checks to see if the module can be loaded. If this fails, then rather than failing tests this skips all tests.

Adds menu items to the R Commander for parametric analysis of dichotomous choice contingent valuation (DCCV) data. CV is a question-based survey method to elicit individuals preferences for goods and services. This package depends on functions regarding parametric DCCV analysis in the package DCchoice. See Carson and Hanemann (2005) <doi:10.1016/S1574-0099(05)02017-6> for DCCV.

Data from the sequencing of a 50/50 mixture of HapMap trio samples NA12878 (CEU) and NA19240 (YRI), subset to the TP53 region.

Filter genetic variants using different criteria such as inheritance model, amino acid change consequence, minor allele frequencies across human populations, splice site strength, conservation, etc.

This minor mode sets background color to strings that match color names, e.g., #0000ff is displayed in white with a blue background.

Method_source retrieves the source code for Ruby methods. Additionally, it can extract source code from Proc and Lambda objects or just extract comments.

An example package which shows use of NLopt functionality from C++ via Rcpp without requiring linking, and relying just on nloptr thanks to the exporting API added there by Jelmer Ypma. This package is a fully functioning, updated, and expanded version of the initial example by Julien Chiquet at <https://github.com/jchiquet/RcppArmadilloNLoptExample> also containing a large earlier pull request of mine.

Estimation of heterogeneity-robust difference-in-differences estimators, with a binary, discrete, or continuous treatment, in designs where past treatments may affect the current outcome.

The main function of the package aims to update lmer()'/'glmer() models depending on their warnings, so trying to avoid convergence and singularity problems.

Supporting data for the seq2patheway package. Includes modified gene sets from MsigDB and org.Hs.eg.db; gene locus definitions from GENCODE project.

Imports Azure Application Insights for web pages into Shiny apps via Microsoft's JavaScript snippet. Allows app developers to submit page tracking and submit events.

Model selection method with multiple block-wise imputation for block-wise missing data; see Xue, F., and Qu, A. (2021) <doi:10.1080/01621459.2020.1751176>.

Uses three different correlation coefficients to calculate measurement-level adequate correlations in a feature matrix: Pearson product-moment correlation coefficient, Intraclass correlation and Cramer's V.

An implementation of the Super Learner prediction algorithm from van der Laan, Polley, and Hubbard (2007) <doi:10.2202/1544-6115.1309 using the mlr3 framework.

Clinical Data Interchange Standards Consortium (CDISC) Standard Data Tabulation Model (SDTM) controlled terminology, 2025-03-25. Source: <https://evs.nci.nih.gov/ftp1/CDISC/SDTM/>.

This package performs exact or approximate adaptive or nonadaptive Cochran-Mantel-Haenszel-Birch tests and sensitivity analyses for one or two 2x2xk tables in observational studies.

This contains the udev rules for trezord. This will let a user run trezord as a regular user instead of needing to it run as root.