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r-eganet
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Implements the Exploratory Graph Analysis (EGA) framework for dimensionality and psychometric assessment. EGA estimates the number of dimensions in psychological data using network estimation methods and community detection algorithms. A bootstrap method is provided to assess the stability of dimensions and items. Fit is evaluated using the Entropy Fit family of indices. Unique Variable Analysis evaluates the extent to which items are locally dependent (or redundant). Network loadings provide similar information to factor loadings and can be used to compute network scores. A bootstrap and permutation approach are available to assess configural and metric invariance. Hierarchical structures can be detected using Hierarchical EGA. Time series and intensive longitudinal data can be analyzed using Dynamic EGA, supporting individual, group, and population level assessments.
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2025-04-22 |
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r-earth
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Build regression models using the techniques in Friedman's papers "Fast MARS" and "Multivariate Adaptive Regression Splines" <doi:10.1214/aos/1176347963>. (The term "MARS" is trademarked and thus not used in the name of the package.)
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2025-04-22 |
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r-dynutils
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Provides common functionality for the 'dynverse' packages. 'dynverse' is created to support the development, execution, and benchmarking of trajectory inference methods. For more information, check out <https://dynverse.org>.
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2025-04-22 |
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r-dynr
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Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous- time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state-space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single-subject time series data or multiple-subject longitudinal data. Ou, Hunter, & Chow (2019) <doi:10.32614%2FRJ-2019-012> provided a detailed introduction to the interface and more information on the algorithms.
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2025-04-22 |
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r-dynsurv
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Time-varying coefficient models for interval censored and right censored survival data including 1) Bayesian Cox model with time-independent, time-varying or dynamic coefficients for right censored and interval censored data studied by Sinha et al. (1999) <doi:10.1111/j.0006-341X.1999.00585.x> and Wang et al. (2013) <doi:10.1007/s10985-013-9246-8>, 2) Spline based time-varying coefficient Cox model for right censored data proposed by Perperoglou et al. (2006) <doi:10.1016/j.cmpb.2005.11.006>, and 3) Transformation model with time-varying coefficients for right censored data using estimating equations proposed by Peng and Huang (2007) <doi:10.1093/biomet/asm058>.
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2025-04-22 |
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r-dtwclust
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Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.
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2025-04-22 |
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r-duckdb
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The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and a R Database Interface (DBI) connector.
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2025-04-22 |
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r-dvmisc
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Contains functions that do something convenient (e.g. create BMI categories), functions for calculating moving-window statistics efficiently, and functions for generating various figures (e.g. histograms with fitted probability mass/density function).
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2025-04-22 |
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r-dse
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Tools for multivariate, linear, time-invariant, time series models. This includes ARMA and state-space representations, and methods for converting between them. It also includes simulation methods and several estimation functions. The package has functions for looking at model roots, stability, and forecasts at different horizons. The ARMA model representation is general, so that VAR, VARX, ARIMA, ARMAX, ARIMAX can all be considered to be special cases. Kalman filter and smoother estimates can be obtained from the state space model, and state-space model reduction techniques are implemented. An introduction and User's Guide is available in a vignette.
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2025-04-22 |
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r-drgee
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Fit restricted mean models for the conditional association between an exposure and an outcome, given covariates. Three methods are implemented: O-estimation, where a nuisance model for the association between the covariates and the outcome is used; E-estimation where a nuisance model for the association between the covariates and the exposure is used, and doubly robust (DR) estimation where both nuisance models are used. In DR-estimation, the estimates will be consistent when at least one of the nuisance models is correctly specified, not necessarily both. For more information, see Zetterqvist and Sjölander (2015) <doi:10.1515/em-2014-0021>.
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2025-04-22 |
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r-drake
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A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://books.ropensci.org/drake/>.
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2025-04-22 |
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r-dplr
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Perform tree-ring analyses such as detrending, chronology building, and cross dating. Read and write standard file formats used in dendrochronology.
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2025-04-22 |
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r-dodgr
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Distances on dual-weighted directed graphs using priority-queue shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed graphs have weights from A to B which may differ from those from B to A. Dual-weighted directed graphs have two sets of such weights. A canonical example is a street network to be used for routing in which routes are calculated by weighting distances according to the type of way and mode of transport, yet lengths of routes must be calculated from direct distances.
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2025-04-22 |
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r-divemove
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Utilities to represent, visualize, filter, analyse, and summarize time-depth recorder (TDR) data. Miscellaneous functions for handling location data are also provided.
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2025-04-22 |
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r-distr
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S4-classes and methods for distributions.
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2025-04-22 |
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r-diversitree
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Contains a number of comparative 'phylogenetic' methods, mostly focusing on analysing diversification and character evolution. Contains implementations of 'BiSSE' (Binary State 'Speciation' and Extinction) and its unresolved tree extensions, 'MuSSE' (Multiple State 'Speciation' and Extinction), 'QuaSSE', 'GeoSSE', and 'BiSSE-ness' Other included methods include Markov models of discrete and continuous trait evolution and constant rate 'speciation' and extinction.
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2025-04-22 |
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r-distrex
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Extends package 'distr' by functionals, distances, and conditional distributions.
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2025-04-22 |
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r-dire
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Fit latent variable linear models, estimating score distributions for groups of people, following Cohen and Jiang (1999) <doi:10.2307/2669917>. In this model, a latent distribution is conditional on students item response, item characteristics, and conditioning variables the user includes. This latent trait is then integrated out. This software is intended to fit the same models as the existing software 'AM' <https://am.air.org/>. As of version 2, also allows the user to draw plausible values.
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2025-04-22 |
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r-dirichletreg
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Implements Dirichlet regression models.
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2025-04-22 |
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r-dipsaus
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Works as an "add-on" to packages like 'shiny', 'future', as well as 'rlang', and provides utility functions. Just like dipping sauce adding flavors to potato chips or pita bread, 'dipsaus' for data analysis and visualizations adds handy functions and enhancements to popular packages. The goal is to provide simple solutions that are frequently asked for online, such as how to synchronize 'shiny' inputs without freezing the app, or how to get memory size on 'Linux' or 'MacOS' system. The enhancements roughly fall into these four categories: 1. 'shiny' input widgets; 2. high-performance computing using the 'future' package; 3. modify R calls and convert among numbers, strings, and other objects. 4. utility functions to get system information such like CPU chip-set, memory limit, etc.
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2025-04-22 |
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r-didimputation
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Estimates Two-way Fixed Effects difference-in-differences/event-study models using the imputation-based approach proposed by Borusyak, Jaravel, and Spiess (2021).
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2025-04-22 |
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r-diceoptim
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Efficient Global Optimization (EGO) algorithm as described in "Roustant et al. (2012)" <doi:10.18637/jss.v051.i01> and adaptations for problems with noise ("Picheny and Ginsbourger, 2012") <doi:10.1016/j.csda.2013.03.018>, parallel infill, and problems with constraints.
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2025-04-22 |
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r-diagis
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Fast functions for effective sample size, weighted multivariate mean, variance, and quantile computation, and weight diagnostic plot for generic importance sampling type or other probability weighted samples.
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2025-04-22 |
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r-detrendr
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Detrend fluorescence microscopy image series for fluorescence fluctuation and correlation spectroscopy ('FCS' and 'FFS') analysis. This package contains functionality published in a 2016 paper <doi:10.1093/bioinformatics/btx434> but it has been extended since then with the Robin Hood algorithm and thus contains unpublished work.
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2025-04-22 |
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r-desctools
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A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.
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2025-04-22 |
