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ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models. Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).
This package provides a port of Ruby Warrior. Teaches R programming in a fun and interactive way.
Assists for presentation and visualization of data from the Norwegian Health Quality Registries following the standardization based on the requirement specified by the National Service for Health Quality Registries. This requirement can be accessed from (<https://www.kvalitetsregistre.no/resultater-til-publisering-pa-nett>). Unfortunately the website is only available in Norwegian.
This package provides tools for response surface analysis, using a comparative framework that identifies best-fitting solutions across 37 families of polynomials. Many of these tools are based upon and extend the RSA package, by testing a larger scope of polynomials (+27 families), more diverse response surface probing techniques (+acceleration points), more plots (+line of congruence, +line of incongruence, both with extrema), and other useful functions for exporting results.
The rank distance correlation <doi:10.1080/01621459.2020.1782223> is computed. Included also is a function to perform permutation based testing.
This package provides functions for detecting spatial clusters using the flexible spatial scan statistic developed by Tango and Takahashi (2005) <doi:10.1186/1476-072X-4-11>. This package implements a wrapper for the C routine used in the FleXScan 3.1.2 <https://sites.google.com/site/flexscansoftware/home> developed by Takahashi, Yokoyama, and Tango. For details, see Otani et al. (2021) <doi:10.18637/jss.v099.i13>.
Inspired by the classic RSA', we developed the improved Generalized Reporter Score-based Analysis (GRSA) method, implemented in the R package ReporterScore', along with comprehensive visualization methods and pathway databases. GRSA is a threshold-free method that works well with all types of biomedical features, such as genes, chemical compounds, and microbial species. Importantly, the GRSA supports multi-group and longitudinal experimental designs, because of the included multi-group-compatible statistical methods.
An interface to the Integrated Taxonomic Information System ('ITIS') (<https://www.itis.gov>). Includes functions to work with the ITIS REST API methods (<https://www.itis.gov/ws_description.html>), as well as the Solr web service (<https://www.itis.gov/solr_documentation.html>).
This package provides a simple WebDAV client that provides functions to fetch and send files or folders to servers using the WebDAV protocol (see RFC 4918 <https://www.rfc-editor.org/rfc/rfc4918>). Only a subset of the protocol is implemented (e.g. file locks are not yet supported).
Utilities for reading, writing, and managing RCDF files, including encryption and decryption support. It offers a flexible interface for handling data stored in encrypted Parquet format, along with metadata extraction, key management, and secure operations using AES and RSA encryptions.
Mass rollup for a Bill of Materials is an example of a class of computations in which elements are arranged in a tree structure and some property of each element is a computed function of the corresponding values of its child elements. Leaf elements, i.e., those with no children, have values assigned. In many cases, the combining function is simple arithmetic sum; in other cases (e.g., mass properties), the combiner may involve other information such as the geometric relationship between parent and child, or statistical relations such as root-sum-of-squares (RSS). This package implements a general function for such problems. It is adapted to specific recursive computations by functional programming techniques; the caller passes a function as the update parameter to rollup() (or, at a lower level, passes functions as the get, set, combine, and override parameters to update_prop()) at runtime to specify the desired operations. The implementation relies on graph-theoretic algorithms from the igraph package of Csárdi, et al. (2006 <doi:10.5281/zenodo.7682609>).
This package provides spatial data analysis functionalities including Exploratory Spatial Data Analysis, Spatial Cluster Detection and Clustering Analysis, Regionalization, etc. based on the C++ source code of GeoDa', which is an open-source software tool that serves as an introduction to spatial data analysis. The GeoDa software and its documentation are available at <https://geodacenter.github.io>.
For the calculation of sample size or power in a two-group repeated measures design, accounting for attrition and accommodating a variety of correlation structures for the repeated measures; details of the method can be found in the scientific paper: Donald Hedeker, Robert D. Gibbons, Christine Waternaux (1999) <doi:10.3102/10769986024001070>.
The Ryan-Holm step-down Bonferroni or Sidak procedure is to control the family-wise (experiment-wise) type I error rate in the multiple comparisons. This procedure provides the adjusting p-values and adjusting CIs. The methods used in this package are referenced from John Ludbrook (2000) <doi:10.1046/j.1440-1681.2000.03223.x>.
This package provides methods from Yeh, Rice, and Dubin (2022) <doi:10.1080/00031305.2021.1967781> for comparing two continuously updated probabilistic forecasts under squared (Brier) loss: pointwise loss and variance, a global delta test (Monte Carlo p-values), simulation designs, and a naive pointwise band plot.
Implemented are an ANOVA-type test statistic for testing hypotheses formulated in Mann-Whitney-type effects in nonparametric factorial designs. Statistical inference is based on a wild or a sample-specific bootstrap approach as described in Dobler et al. (2019) <doi:10.1007/s10463-019-00717-3>'. The unweighted treatment effects considered do not depend on sample sizes and allow for transitive ordering. The package thus provides an extension of the univariate rankFD package to multivariate data.
The lightweight header-only C++-20 logging library spdlite', a lighter version of spdlog and also written by Gabi Melman, provides most of the features of the larger version, and also includes fmt as a fallback if std::format() is not selected.
Adaptation of the Matlab tsEVA toolbox developed by Lorenzo Mentaschi available here: <https://github.com/menta78/tsEva>. It contains an implementation of the Transformed-Stationary (TS) methodology for non-stationary extreme value Analysis (EVA) as described in Mentaschi et al. (2016) <doi:10.5194/hess-20-3527-2016>. In synthesis this approach consists in: (i) transforming a non-stationary time series into a stationary one to which the stationary extreme value theory can be applied; and (ii) reverse-transforming the result into a non-stationary extreme value distribution. RtsEva offers several options for trend estimation (mean, extremes, seasonal) and contains multiple plotting functions displaying different aspects of the non-stationarity of extremes.
This is a port of Jonathan Shewchuk's Triangle library to R. From his description: "Triangle generates exact Delaunay triangulations, constrained Delaunay triangulations, conforming Delaunay triangulations, Voronoi diagrams, and high-quality triangular meshes. The latter can be generated with no small or large angles, and are thus suitable for finite element analysis.".
Make your phrase or sentence into something funny! Pass a string with the keywords in, and get out a bit of humor.
Offers a suite of tools designed to enhance the responsiveness and interactivity of web-based documents and applications created with R. It provides an automatic, configurable resizing toolbar that can be seamlessly integrated with HTML elements such as containers, images, and tables, allowing end-users to dynamically adjust their dimensions. Beyond the toolbar, the package includes a rich collection of flexible, expandable, and interactive container functionalities, such as highly customizable split-screen layouts (splitCard), versatile sizeable cards (sizeableCard), dynamic window-like elements (windowCard), visually engaging emphasis cards (empahsisCard), and sophisticated flexible and elastic card layouts (flexCard, elastiCard). Furthermore, it offers an elegant image viewer and resizer (shinyExpandImage) perfect for interactive galleries. r2resize is particularly well-suited for developers and data scientists looking to create modern, responsive, and user-friendly shiny applications, markdown reports, and quarto documents that adapt gracefully to different screen sizes and user preferences, significantly improving the user experience.
This package performs exact rate ratio tests.
This package provides methods for Resampling-based False Discovery Proportion control. A function is provided that provides simultaneous, multi-resolution False Discovery Exceedance (FDX) control as described in Hemerik (2025) <doi:10.48550/arXiv.2509.02376>.
Function for generating random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.