Conduct simulations of the Response Adaptive Block Randomization (RABR) design to evaluate its type I error rate, power and operating characteristics for binary and continuous endpoints. For more details of the proposed method, please refer to Zhan et al. (2021) <doi:10.1002/sim.9104>.

Providing the container for the DockerParallel package.

This package provides a simple data science challenge system using R Markdown and Dropbox <https://www.dropbox.com/>. It requires no network configuration, does not depend on external platforms like e.g. Kaggle <https://www.kaggle.com/> and can be easily installed on a personal computer.

Computes a variety of statistics for relational event models. Relational event models enable researchers to investigate both exogenous and endogenous factors influencing the evolution of a time-ordered sequence of events. These models are categorized into tie-oriented models (Butts, C., 2008, <doi:10.1111/j.1467-9531.2008.00203.x>), where the probability of a dyad interacting next is modeled in a single step, and actor-oriented models (Stadtfeld, C., & Block, P., 2017, <doi:10.15195/v4.a14>), which first model the probability of a sender initiating an interaction and subsequently the probability of the sender's choice of receiver. The package is designed to compute a variety of statistics that summarize exogenous and endogenous influences on the event stream for both types of models.

Algorithms for solving a self-calibrated l1-regularized quadratic programming problem without parameter tuning. The algorithm, called DECODE, can handle high-dimensional data without cross-validation. It is found useful in high dimensional portfolio selection (see Pun (2018) <https://ssrn.com/abstract=3179569>) and large precision matrix estimation and sparse linear discriminant analysis (see Pun and Hadimaja (2019) <https://ssrn.com/abstract=3422590>).

This package provides a toolkit for making antigenic maps from immunological assay data, in order to quantify and visualize antigenic differences between different pathogen strains as described in Smith et al. (2004) <doi:10.1126/science.1097211> and used in the World Health Organization influenza vaccine strain selection process. Additional functions allow for the diagnostic evaluation of antigenic maps and an interactive viewer is provided to explore antigenic relationships amongst several strains and incorporate the visualization of associated genetic information.

This package provides randomization tests and graphical diagnostics for assessing randomized assignment and covariate balance for a binary treatment variable. See Branson (2021) <arXiv:1804.08760> for details.

Routines to select and visualize the maxima for a given strict partial order. This especially includes the computation of the Pareto frontier, also known as (Top-k) Skyline operator (see Börzsönyi, et al. (2001) <doi:10.1109/ICDE.2001.914855>), and some generalizations known as database preferences (see Kieà ling (2002) <doi:10.1016/B978-155860869-6/50035-4>).

Feasible multivariate GARCH models including DCC, GO-GARCH and Copula-GARCH.

Build regular expressions piece by piece using human readable code. This package contains date and time functionality, and is primarily intended to be used by package developers.

Implementation of Gibbs sampling algorithm for Bayesian Estimation of the Reduced Reparameterized Unified Model ('rrum'), described by Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.

Constrained clustering, transfer functions, and other methods for analysing Quaternary science data.

Includes algorithms to facilitate the assessment of extinction risk of species according to the IUCN (International Union for Conservation of Nature, see <https://iucn.org/> for more information) red list criteria.

Data objects in R can be rendered as HTML tables using the JavaScript library ag-grid (typically via R Markdown or Shiny'). The ag-grid library has been included in this R package. The package name RagGrid is an abbreviation of R agGrid'.

This package provides the robust gamma rank correlation coefficient as introduced by Bodenhofer, Krone, and Klawonn (2013) <DOI:10.1016/j.ins.2012.11.026> along with a permutation-based rank correlation test. The rank correlation coefficient and the test are explicitly designed for dealing with noisy numerical data.

This package provides a framework for creating high-performance R packages powered by the Rust programming language using the extendr Rust crate. It offers usethis'-like functions to scaffold and develop Rust powered R packages, including utilities for publishing to CRAN, managing dependencies, configuring development environments, and rendering Rust code in knitr documents. Additionally, it provides functions to compile and evaluate Rust code directly from R for interactive development.

This package provides tools for filtering occurrence records, generating alpha-hull-derived range polygons and mapping species distributions.

Use R to interface with the TD Ameritrade API <https://developer.tdameritrade.com/>. Functions include authentication, trading, price requests, account information, and option chains. A user will need a TD brokerage account and TD Ameritrade developer app. See README for authentication process and examples.

The visualization tool offers a nuanced understanding of regression dynamics, going beyond traditional per-unit interpretation of continuous variables versus categorical ones. It highlights the impact of unit changes as well as larger shifts like interquartile changes, acknowledging the distribution of empirical data. Furthermore, it generates visualizations depicting alterations in Odds Ratios for predictors across minimum, first quartile, median, third quartile, and maximum values, aiding in comprehending predictor-outcome interplay within empirical data distributions, particularly in logistic regression frameworks.

Fit statistical models based on the Dawid-Skene model - Dawid and Skene (1979) <doi:10.2307/2346806> - to repeated categorical rating data. Full Bayesian inference for these models is supported through the Stan modelling language. rater also allows the user to extract and plot key parameters of these models.

Measuring information flow between time series with Shannon and Rényi transfer entropy. See also Dimpfl and Peter (2013) <doi:10.1515/snde-2012-0044> and Dimpfl and Peter (2014) <doi:10.1016/j.intfin.2014.03.004> for theory and applications to financial time series. Additional references can be found in the theory part of the vignette.

This package implements TRACDS (Temporal Relationships between Clusters for Data Streams), a generalization of Extensible Markov Model (EMM). TRACDS adds a temporal or order model to data stream clustering by superimposing a dynamically adapting Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN data stream clustering). Development of this package was supported in part by NSF IIS-0948893 and R21HG005912 from the National Human Genome Research Institute. Hahsler and Dunham (2010) <doi:10.18637/jss.v035.i05>.

Implementation of the metalog distribution in R. The metalog distribution is a modern, highly flexible, data-driven distribution. Metalogs are developed by Keelin (2016) <doi:10.1287/deca.2016.0338>. This package provides functions to build these distributions from raw data. Resulting metalog objects are then useful for exploratory and probabilistic analysis.

Implementation of Taylor Regression Estimator (TRE), Tulip Extreme Finding Estimator (TEFE), Bell Extreme Finding Estimator (BEFE), Integration Extreme Finding Estimator (IEFE) and Integration Root Finding Estimator (IRFE) for roots, extrema and inflections of a curve . Christopoulos, DT (2019) <doi:10.13140/RG.2.2.17158.32324> . Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076> . Christopoulos, DT (2016) <https://demovtu.veltech.edu.in/wp-content/uploads/2016/04/Paper-04-2016.pdf> . Christopoulos, DT (2014) <doi:10.48550/arXiv.1206.5478> .