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This package provides utilities to calculate the probabilities of various dice-rolling events, such as the probability of rolling a four-sided die six times and getting a 4, a 3, and either a 1 or 2 among the six rolls (in any order); the probability of rolling two six-sided dice three times and getting a 10 on the first roll, followed by a 4 on the second roll, followed by anything but a 7 on the third roll; or the probabilities of each possible sum of rolling five six-sided dice, dropping the lowest two rolls, and summing the remaining dice.
This package performs detection of Differential Item Functioning using the method DIFboost as proposed by Schauberger and Tutz (2016) <doi:10.1111/bmsp.12060>.
Dominance analysis relative importance methods that are intended for predictive models.
Using a Gaussian copula approach, this package generates simulated data mimicking a target real dataset. It supports normal, Poisson, empirical, and DESeq2 (negative binomial with size factors) marginal distributions. It uses an low-rank plus diagonal covariance matrix to efficiently generate omics-scale data. Methods are described in: Yang, Grant, and Brooks (2025) <doi:10.1101/2025.01.31.634335>.
This MCMC method takes a data numeric vector (Y) and assigns the elements of Y to a (potentially infinite) number of normal distributions. The individual normal distributions from a mixture of normals can be inferred. Following the method described in Escobar (1994) <doi:10.2307/2291223> we use a Dirichlet Process Prior (DPP) to describe stochastically our prior assumptions about the dimensionality of the data.
Overload utils::'? to build unary and binary operators from existing functions, piping operators of different precedence, and flexible syntaxes.
An open, multi-algorithmic pipeline for easy, fast and efficient analysis of cellular sub-populations and the molecular signatures that characterize them. The pipeline consists of four successive steps: data pre-processing, cellular clustering with pseudo-temporal ordering, defining differential expressed genes and biomarker identification. More details on Ghannoum et. al. (2021) <doi:10.3390/ijms22031399>. This package implements extensions of the work published by Ghannoum et. al. (2019) <doi:10.1101/700989>.
Low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte Carlo methods as described in Solymos 2010 <doi:10.32614/RJ-2010-011>. Sequential and parallel MCMC support for JAGS', WinBUGS', OpenBUGS', and Stan'.
This package provides a shiny application to compute daily and cumulative degree-days from minimum and maximum temperatures using average, single triangle, and single sine methods, with optional upper temperature thresholds. The application maps cumulative thermal accumulation to user-defined developmental stage thresholds and supports exporting tabular and graphical outputs. The degree-day approach follows assumptions described by Higley et al. (1986) <doi:10.1093/ee/15.5.999>.
Data and miscellanea to support the book "Introduction to Data analysis with R for Forensic Scientists." This book was written by James Curran and published by CRC Press in 2010 (ISBN: 978-1-4200-8826-7).
Diagnostic tools for auditing data analysis workflows built on data.table'. Provides functions to validate join operations, compare data.tables, filter with diagnostic output, summarize data quality, check primary keys and variable relationships, and diagnose string columns. Designed to help analysts understand and document data transformations.
Decodes meshes and point cloud data encoded by the Draco mesh compression library from Google. Note that this is only designed for basic decoding and not intended as a full scale wrapping of the Draco library.
This package contains data sets, examples and software from the book Design of Observational Studies by Paul R. Rosenbaum, New York: Springer, <doi:10.1007/978-1-4419-1213-8>, ISBN 978-1-4419-1212-1.
This package implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. Reference: Li et al. (2023) <arXiv:2306.04700>.
Builds interactive d3.js hierarchical visualisation easily. D3partitionR makes it easy to build and customize sunburst, circle treemap, treemap, partition chart, ...
It allows to learn the structure of univariate time series, learning parameters and forecasting. Implements a model of Dynamic Bayesian Networks with temporal windows, with collections of linear regressors for Gaussian nodes, based on the introductory texts of Korb and Nicholson (2010) <doi:10.1201/b10391> and Nagarajan, Scutari and Lèbre (2013) <doi:10.1007/978-1-4614-6446-4>.
Fast & memory-efficient functions to analyze and manipulate large spatial data data sets. It leverages the fast analytical capabilities of DuckDB and its spatial extension (see <https://duckdb.org/docs/stable/core_extensions/spatial/overview>) while maintaining compatibility with Râ s spatial data ecosystem to work with spatial vector data.
Populate data from an R environment into .doc and .docx templates. Create a template document in a program such as Word', and add strings encased in guillemet characters to create flags («example»). Use getDictionary() to create a dictionary of flags and replacement values, then call docket() to generate a populated document.
Offers statistical methods to compare diagnostic performance between two binary diagnostic tests on the same subject in clinical studies. Includes functions for generating formatted tables to display diagnostic outcomes, facilitating a clear and comprehensive comparison directly through the R console. Inspired by and extending the functionalities of the DTComPair', tableone', and gtsummary packages.
This package provides select, insert, update, upsert, and delete database operations. Supports PostgreSQL', MySQL', SQLite', and more, and plays nicely with the DBI package.
Monthly download stats of CRAN and Bioconductor packages. Download stats of CRAN packages is from the RStudio CRAN mirror', see <https://cranlogs.r-pkg.org:443>. Bioconductor package download stats is at <https://bioconductor.org/packages/stats/>.
This package provides a general framework using mixture Weibull distributions to accurately predict biomarker-guided trial duration accounting for heterogeneous population. Extensive simulations are performed to evaluate the impact of heterogeneous population and the dynamics of biomarker characteristics and disease on the study duration. Several influential parameters including median survival time, enrollment rate, biomarker prevalence and effect size are identified. Efficiency gains of biomarker-guided trials can be quantitatively compared to the traditional all-comers design. For reference, see Zhang et al. (2024) <arXiv:2401.00540>.
An R interface to the Free Dictionary API <https://dictionaryapi.dev/>, <https://github.com/meetDeveloper/freeDictionaryAPI>. Retrieve dictionary definitions for English words, as well as additional information including phonetics, part of speech, origins, audio pronunciation, example usage, synonyms and antonyms, returned in tidy format for ease of use.
This package provides extra functions to manipulate dendrograms that build on the base functions provided by the stats package. The main functionality it is designed to add is the ability to colour all the edges in an object of class dendrogram according to cluster membership i.e. each subtree is coloured, not just the terminal leaves. In addition it provides some utility functions to cut dendrogram and hclust objects and to set/get labels.