Routines for flexible functional form estimation via basis regression, with model selection via the adaptive LASSO or SCAD to prevent overfitting.

The goal of planets is to provide of very simple and accessible data containing basic information from all known planets.

Creates, fits and samples Pair-Copula Bayesian networks (PCBN) under some restrictions on the underlying Directed Acyclic Graph (DAG), that is, no active cycles nor interfering v-structures, following Derumigny, Horsman and Kurowicka (2025) <doi:10.48550/arXiv.2510.03518>.

Set of functions that implement the PoDBAY method, described in the publication A method to estimate probability of disease and vaccine efficacy from clinical trial immunogenicity data by Julie Dudasova, Regina Laube, Chandni Valiathan, Matthew C. Wiener, Ferdous Gheyas, Pavel Fiser, Justina Ivanauskaite, Frank Liu and Jeffrey R. Sachs (NPJ Vaccines, 2021), <doi:10.1038/s41541-021-00377-6>.

Based on different statistical definitions of discrimination, several methods have been proposed to detect and mitigate social inequality in machine learning models. This package aims to provide an alternative to fairness treatment in predictive models. The ROC method implemented in this package is described by Kamiran, Karim and Zhang (2012) <https://ieeexplore.ieee.org/document/6413831/>.

Create and customize interactive phylogenetic trees using the phylocanvas JavaScript library and the htmlwidgets package. These trees can be used directly from the R console, from RStudio', in Shiny apps, and in R Markdown documents. See <http://phylocanvas.org/> for more information on the phylocanvas library.

This package provides functions for calculating and analyzing the proliferative index (PI) from an RNA-seq dataset. As described in Ramaker & Lasseigne, et al. bioRxiv, 2016 <doi:10.1101/063057>.

Control Philips Hue smart lighting. Use this package to connect to a Hue bridge on your local network (remote authentication not yet supported) and control your smart lights through the Philips Hue API. All API V1 endpoints are supported. See API documentation at <https://developers.meethue.com/>.

Generation of a chosen number of count, binary, ordinal, and continuous random variables, with specified correlations and marginal properties. The details of the method are explained in Demirtas (2012) <DOI:10.1002/sim.5362>.

Most of the time floating point arithmetic does approximately the right thing. When adding sums or having products of numbers that greatly differ in magnitude, the floating point arithmetic may be incorrect. This package implements the Kahan (1965) sum <doi:10.1145/363707.363723>, Neumaier (1974) sum <doi:10.1002/zamm.19740540106>, pairwise-sum (adapted from NumPy', See Castaldo (2008) <doi:10.1137/070679946> for a discussion of accuracy), and arbitrary precision sum (adapted from the fsum in Python ; Shewchuk (1997) <https://people.eecs.berkeley.edu/~jrs/papers/robustr.pdf>). In addition, products are changed to long double precision for accuracy, or changed into a log-sum for accuracy.

Computes probability-scale residuals and residual correlations for continuous, ordinal, binary, count, and time-to-event data Qi Liu, Bryan Shepherd, Chun Li (2020) <doi:10.18637/jss.v094.i12>.

Read depth data from genotyping-by-sequencing (GBS) or restriction site-associated DNA sequencing (RAD-seq) are imported and used to make Bayesian probability estimates of genotypes in polyploids or diploids. The genotype probabilities, posterior mean genotypes, or most probable genotypes can then be exported for downstream analysis. polyRAD is described by Clark et al. (2019) <doi:10.1534/g3.118.200913>, and the Hind/He statistic for marker filtering is described by Clark et al. (2022) <doi:10.1186/s12859-022-04635-9>. A variant calling pipeline for highly duplicated genomes is also included and is described by Clark et al. (2020, Version 1) <doi:10.1101/2020.01.11.902890>.

Interactively explore various dependencies of a package(s) (on the Comprehensive R Archive Network Like repositories) and perform analysis using tidy philosophy. Most of the functions return a tibble object (enhancement of dataframe') which can be used for further analysis. The package offers functions to produce network and igraph dependency graphs. The plot method produces a static plot based on ggnetwork and plotd3 function produces an interactive D3 plot based on networkD3'.

Perform sample size, power calculation and subsequent analysis for Immuno-oncology (IO) trials composed of responders and non-responders.

Simulate the dynamic of lion populations using a specific Individual-Based Model (IBM) compiled in C.

This package provides a set of Analysis Data Model (ADaM) datasets constructed by modifying the ADaM datasets in the pharmaverseadam package to meet J&J Innovative Medicine's standard data structure for Clinical and Statistical Programming.

This provides utilities for creating classed error and warning conditions based on where the error originated.

This package provides a user friendly way to create patient level prediction models using the Observational Medical Outcomes Partnership Common Data Model. Given a cohort of interest and an outcome of interest, the package can use data in the Common Data Model to build a large set of features. These features can then be used to fit a predictive model with a number of machine learning algorithms. This is further described in Reps (2017) <doi:10.1093/jamia/ocy032>.

Check a data frame for personal information, including names, location, disability status, and geo-coordinates.

Convert English letters to numbers or numbers to English letters as on a telephone keypad. When converting letters to numbers, a character vector is returned with "A," "B," or "C" becoming 2, "D," "E", or "F" becoming 3, etc. When converting numbers to letters, a character vector is returned with multiple elements (i.e., "2" becomes a vector of "A," "B," and "C").

This package implements the Single Transferable Vote (STV) electoral system, with clear explanatory graphics. The core function stv() uses Meek's method, the purest expression of the simple principles of STV, but which requires electronic counting. It can handle votes expressing equal preferences for subsets of the candidates. A function stv.wig() implementing the Weighted Inclusive Gregory method, as used in Scottish council elections, is also provided, and with the same options, as described in the manual. The required vote data format is as an R list: a function pref.data() is provided to transform some commonly used data formats into this format. References for methodology: Hill, Wichmann and Woodall (1987) <doi:10.1093/comjnl/30.3.277>, Hill, David (2006) <https://www.votingmatters.org.uk/ISSUE22/I22P2.pdf>, Mollison, Denis (2023) <arXiv:2303.15310>, (see also the package manual pref_pkg_manual.pdf).

This package provides additional functions for evaluating predictive models, including plotting calibration curves and model-based Receiver Operating Characteristic (mROC) based on Sadatsafavi et al (2021) <arXiv:2003.00316>.

The semiparametric accelerated failure time (AFT) model is an attractive alternative to the Cox proportional hazards model. This package provides a suite of functions for fitting one popular rank-based estimator of the semiparametric AFT model, the regularized Gehan estimator. Specifically, we provide functions for cross-validation, prediction, coefficient extraction, and visualizing both trace plots and cross-validation curves. For further details, please see Suder, P. M. and Molstad, A. J., (2022) Scalable algorithms for semiparametric accelerated failure time models in high dimensions, Statistics in Medicine <doi:10.1002/sim.9264>.

Read and write GraphPad Prism .pzfx files in R.