Provide reproducible R chunks in R Markdown document that automatically check computational results for reproducibility. This is achieved by creating json files storing metadata about computational results. A comprehensive tutorial to the package is available as preprint by Brandmaier & Peikert (2024, <doi:10.31234/osf.io/3zjvf>).

The goal of the rbrsa package is to provide automated access to banking sector data from the Turkish Banking Regulation and Supervision Agency (BRSA, known as BDDK in Turkish). The package retrieves tables from two distinct publication portals maintained by the BRSA: The Monthly Bulletin Portal <https://www.bddk.org.tr/bultenaylik> and The FinTurk Data System <https://www.bddk.org.tr/BultenFinturk>.

Bundles the datasets and functions featured in Philip H. Pollock and Barry C. Edwards<https://edge.sagepub.com/pollock>, "An R Companion to Political Analysis, 3rd Edition," Thousand Oaks, CA: Sage Publications.

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

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.

Collection of tools for the analysis of the resilience of dynamic networks. Created as a classroom project.

Enables the calibration and analysis of radiocarbon dates, often but not exclusively for the purposes of archaeological research. It includes functions not only for basic calibration, uncalibration, and plotting of one or more dates, but also a statistical framework for building demographic and related longitudinal inferences from aggregate radiocarbon date lists, including: Monte-Carlo simulation test (Timpson et al 2014 <doi:10.1016/j.jas.2014.08.011>), random mark permutation test (Crema et al 2016 <doi:10.1371/journal.pone.0154809>) and spatial permutation tests (Crema, Bevan, and Shennan 2017 <doi:10.1016/j.jas.2017.09.007>).

Generate SpatRaster objects, as defined by the terra package, from digital images, using a specified spatial object as a geographical reference.

The quantitative measurement and detection of molecules in HPLC should be carried out by an accurate description of chromatographic peaks. In this package non-linear fitting using a modified Gaussian model with a parabolic variance (PVMG) has been implemented to obtain the retention time and height at the peak maximum. This package also includes the traditional Van Deemter approach and two alternatives approaches to characterize chromatographic column.

This package provides a collection of high-level, machine- and OS-independent tools for making reproducible and reusable content in R. The two workhorse functions are Cache() and prepInputs()'. Cache() allows for nested caching, is robust to environments and objects with environments (like functions), and deals with some classes of file-backed R objects e.g., from terra and raster packages. Both functions have been developed to be foundational components of data retrieval and processing in continuous workflow situations. In both functions, efforts are made to make the first and subsequent calls of functions have the same result, but faster at subsequent times by way of checksums and digesting. Several features are still under development, including cloud storage of cached objects allowing for sharing between users. Several advanced options are available, see ?reproducibleOptions()'.

This package provides functions for studying realized genetic relatedness between people. Users will be able to simulate inheritance patterns given pedigree structures, generate SNP marker data given inheritance patterns, and estimate realized relatedness between pairs of individuals using SNP marker data. See Wang (2017) <doi:10.1534/genetics.116.197004>. This work was supported by National Institutes of Health grants R37 GM-046255.

This package provides a tool to read and manipulate data generated from RiverWare'(TM) <https://www.riverware.org/> simulations. RiverWare and RiverSMART generate data in "rdf", "csv", and "nc" format. This package provides an interface to read, aggregate, and summarize data from one or more simulations in a dplyr pipeline.

Generate causally-simulated data to serve as ground truth for evaluating methods in causal discovery and effect estimation. The package provides tools to assist in defining functions based on specified edges, and conversely, defining edges based on functions. It enables the generation of data according to these predefined functions and causal structures. This is particularly useful for researchers in fields such as artificial intelligence, statistics, biology, medicine, epidemiology, economics, and social sciences, who are developing a general or a domain-specific methods to discover causal structures and estimate causal effects. Data simulation adheres to principles of structural causal modeling. Detailed methodologies and examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rcausim/blob/master/doc/causal_simulation_exemplar.html>.

This package provides a bagging predictor based on generalized linear models (GLMs) is implemented. The method is published in Song, Langfelder and Horvath (2013) <doi:10.1186/1471-2105-14-5>.

Predicting regulatory DNA elements based on epigenomic signatures. This package is more of a set of building blocks than a direct solution. REPTILE regulatory prediction pipeline is built on this R package. See <https://github.com/yupenghe/REPTILE> for more information.

Load data from Yandex Direct API V5 <https://yandex.ru/dev/direct/doc/dg/concepts/about-docpage> into R. Provide function for load lists of campaings, ads, keywords and other objects from Yandex Direct account. Also you can load statistic from API Reports Service <https://yandex.ru/dev/direct/doc/reports/reports-docpage>. And allows keyword bids management.

Configuration management using files (YAML, JSON, INI, TXT), JSON strings, and command line arguments. Command line arguments can be used to override configuration. Period-separated command line flags are parsed as hierarchical lists. Environment variables, R global variables, and configuration values can be substituted.

This package provides a trimmed down copy of the "kent-core source tree" turned into a C library for manipulation of .2bit files. See <https://genome.ucsc.edu/FAQ/FAQformat.html#format7> for a quick overview of the 2bit format. The "kent-core source tree" can be found here: <https://github.com/ucscGenomeBrowser/kent-core/>. Only the .c and .h files from the source tree that are related to manipulation of .2bit files were kept. Note that the package is primarily useful to developers of other R packages who wish to use the 2bit C library in their own C'/'C++ code.

Calculate common survey data quality indicators for multi-item scales and matrix questions. Currently supports the calculation of response style indicators and response distribution indicators. For an overview on response quality indicators see Bhaktha N, Henning S, Clemens L (2024). Characterizing response quality in surveys with multi-item scales: A unified framework <https://osf.io/9gs67/>.

The TRIM model is widely used for estimating growth and decline of animal populations based on (possibly sparsely available) count data. The current package is a reimplementation of the original TRIM software developed at Statistics Netherlands by Jeroen Pannekoek. See <https://www.cbs.nl/en-gb/society/nature-and-environment/indices-and-trends%2d%2dtrim%2d%2d> for more information about TRIM.

Creation, manipulation, simulation of linear Gaussian Bayesian networks from text files and more...

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.

This package provides a simple approach to configuring R projects with different parameter values. Configurations are specified using a reduced subset of base R and parsed accordingly.

R Markdown output formats based on JavaScript libraries such as Scrollama (<https://github.com/russellsamora/scrollama>) for storytelling.