Enables the usage of the OpenDota API from <https://www.opendota.com/>, get game lists, and download JSON's of parsed replays from the OpenDota API. Also has functionality to execute own code to extract the specific parts of the JSON file.

This package provides a framework for defining pipelines of functions for applying data transformations, model estimation and inverse-transformations, resulting in predicted value generation (or model-scoring) functions that automatically apply the entire pipeline of functions required to go from input to predicted output.

This package provides tools for converting statistical results into consistent, publication-ready character output. Current functionality includes formatting p-values, confidence intervals, and correlation coefficients using publication-friendly conventions. The package emphasizes consistent reporting while preserving the underlying statistical results and statistical decision-making.

Search CRAN metadata about packages by keyword, popularity, recent activity, package name and more. Uses the R-hub search server, see <https://r-pkg.org> and the CRAN metadata database, that contains information about CRAN packages. Note that this is _not_ a CRAN project.

Adds an LLM-powered chatbot to your shiny app, that can turn your users natural language questions into SQL queries that run against your data, and return the result as a reactive data frame. Use it to drive reactive calculations, visualizations, downloads, and more.

Computes kernel-smoothed receiver operating characteristic (ROC) curves and area under the curve (AUC), including confidence intervals, using several bandwidth selection methods. Also provides the Youden index with confidence intervals, the Youden point, and optimal diagnostic cutoff estimation. Supports Gaussian, Biweight, and Epanechnikov kernels.

Users may specify what fundamental qualities of a new study have or have not changed in an attempt to reproduce or replicate an original study. A comparison of the differences is visualized. Visualization approach follows Patil', Peng', and Leek (2016) <doi:10.1101/066803>.

Fits symmetric soft windowing to linear and non-linear models by assigning exponential weights over time around specified modes; bandwidth and sharpness of the windows are chosen by a grid search and comparison diagnostics (Hamed Haselimashhadi et al (2019) <doi:10.1093/bioinformatics/btz744>).

Visualize long timelines, extended sequences and temporally chained survey responses and experience sampling data using intuitive serpentine (snake) plots. Supports distribution bars, tick-mark plots, inter-item correlation arcs, faceted multi-construct panels, and daily time-of-day positioning for ecological momentary assessment data.

Statistical methods for estimating and inferring the mean of functional data. The methods include simultaneous confidence bands, local polynomial fitting, bandwidth selection by plug-in and cross-validation, goodness-of-fit tests for parametric models, equality tests for two-sample problems, and plotting functions.

This package provides a tool to create and style HTML tables with CSS. These can be exported and used in any application that accepts HTML (e.g. shiny', rmarkdown', PowerPoint'). It also provides functions to create CSS files (which also work with shiny).

This package provides a tool for building projects that are visually consistent, accessible, and easy to maintain. It provides functions for managing branding assets, applying organization-wide themes using brand.yml', and setting up new projects with accessibility features and correct branding. It supports quarto', shiny', and rmarkdown projects, and integrates with ggplot2'. The accessibility features are based on the Web Content Accessibility Guidelines <https://www.w3.org/WAI/WCAG22/quickref/?versions=2.1> and Accessible Rich Internet Applications (ARIA) specifications <https://www.w3.org/WAI/ARIA/apg/>. The branding framework implements the brand.yml specification <https://posit-dev.github.io/brand-yml/>.

The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.

This package provides tools to create interactive chords diagrams via the D3 Javascript library. Chord diagrams show directed relationships among a group of entities. This package is based on http://bl.ocks.org/mbostock/4062006 with some modifications (fading) and additions (tooltips, bipartite diagram type).

This package contains the function ggsurvplot() for easily drawing beautiful and 'ready-to-publish' survival curves with the 'number at risk' table and 'censoring count plot'. Other functions are also available to plot adjusted curves for Cox model and to visually examine Cox model assumptions.

Solve optimal transport problems. Compute Wasserstein distances (a.k.a. Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p distances), return the corresponding transference plans, and display them graphically. Objects that can be compared include grey-scale images, (weighted) point patterns, and mass vectors.

The main functions for methylGSA are methylglm and methylRRA. methylGSA implements logistic regression adjusting number of probes as a covariate. methylRRA adjusts multiple p-values of each gene by Robust Rank Aggregation. For more detailed help information, please see the vignette.

This package performs Bayesian estimation of the additive main effects and multiplicative interaction (AMMI) model. The method is explained in Crossa, J., Perez-Elizalde, S., Jarquin, D., Cotes, J.M., Viele, K., Liu, G. and Cornelius, P.L. (2011) (<doi:10.2135/cropsci2010.06.0343>).

An implementation of robust estimation in Cox model. Functionality includes fitting efficiently and robustly Cox proportional hazards regression model in its basic form, where explanatory variables are time independent with one event per subject. Method is based on a smooth modification of the partial likelihood.

This package provides tools for linear fitting with complex variables. Includes ordinary least-squares (zlm()) and robust M-estimation (rzlm()), and complex methods for oft used generics. Originally adapted from the rlm() functions of MASS and the lm() functions of stats'.

Utility functions to facilitate the import, the reporting and analysis of clinical data. Example datasets in SDTM and ADaM format, containing a subset of patients/domains from the CDISC Pilot 01 study are also available as R datasets to demonstrate the package functionalities.

This package provides a consistent interface for connecting R to various data sources including file systems and databases. Designed for clinical research, connector streamlines access to ADAM', SDTM for example. It helps to deal with multiple data formats through a standardized API and centralized configuration.

Estimates piecewise linear spline models for assessing temporal trends in cancer incidence and mortality rates. Provides tools for identifying and reporting knot locations, annual percent changes (APCs), and average annual percent changes (AAPCs), facilitating the analysis and communication of changes in cancer rates over time.

We propose an objective Bayesian algorithm for searching the space of Gaussian directed acyclic graph (DAG) models. The algorithm uses moment fractional Bayes factors (MFBF) and is suitable for learning sparse graphs. The algorithm is implemented using Armadillo, an open-source C++ linear algebra library.