Read and write Matlab MAT files from R. The rmatio package supports reading MAT version 4, MAT version 5 and MAT compressed version 5. The rmatio package can write version 5 MAT files and version 5 files with variable compression.

This package provides functions for connecting to BioUML server, querying BioUML repository and launching BioUML analyses.

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>.

This package provides a translation layer between R and CDO operators. Each operator is it's own function with documentation. Nested or piped functions will be translated into CDO chains.

Streamline the calculation of conditional probabilities for various numeric ranges in an R DataFrame. It automates the need to convert numerical data into categorical data for conditional probability calculation, making it ideal for quick and preliminary data analysis.

Import REDATAM formats into R via the Open REDATAM C++ library. The full context of this project and details about the implementation are available in <doi:10.1017/dap.2025.4> (Open Access).

Connects dataframes/tables with a remote data source. Raw data downloaded from the data source can be further processed and transformed using data preparation code that is also baked into the dataframe/table. Refreshable dataframes can be shared easily (e.g. as R data files). Their users do not need to care about the inner workings of the data update mechanisms.

Statistical distribution in OOP (Object Oriented Programming) way. This package proposes a R6 class interface to classic statistical distribution, and new distributions can be easily added with the class AbstractDist. A useful point is the generic fit() method for each class, which uses a maximum likelihood estimation to find the parameters of a dataset, see, e.g. Hastie, T. and al (2009) <isbn:978-0-387-84857-0>. Furthermore, the rv_histogram class gives a non-parametric fit, with the same accessors that for the classic distribution. Finally, three random generators useful to build synthetic data are given: a multivariate normal generator, an orthogonal matrix generator, and a symmetric positive definite matrix generator, see Mezzadri, F. (2007) <arXiv:math-ph/0609050>.

Allows users to import data files containing heartbeat positions in the most broadly used formats, to remove outliers or points with unacceptable physiological values present in the time series, to plot HRV data, and to perform time domain, frequency domain and nonlinear HRV analysis. See Garcia et al. (2017) <DOI:10.1007/978-3-319-65355-6>.

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.

This package provides a simplified version of the Portal Project Database designed for teaching. It provides a real world example of life-history, population, and ecological data, with sufficient complexity to teach many aspects of data analysis and management, but with many complexities removed to allow students to focus on the core ideas and skills being taught. The full database (which should be used for research) is available at <https://github.com/weecology/PortalData>.

The Stochastic Dominance (SD) is the classical way of comparing two random prospects, using their distribution functions. Almost Stochastic Dominance (ASD) has also been developed to cover the SD failures due to the extreme utility functions. This package focuses on classical and heuristic methods for testing the first and second SD and ASD methods given the probability mass function (PMF) of the random prospects. The goal is to apply these methods easily, efficiently, and effectively on real-world datasets. For more details see Hanoch and Levy (1969) <doi:10.2307/2296431>, Leshno and Levy (2002) <doi:10.1287/mnsc.48.8.1074.169>, and Tzeng et al. (2012) <doi:10.1287/mnsc.1120.1616>.

An R interface for processing concentration-response datasets using Curvep, a response noise filtering algorithm. The algorithm was described in the publications (Sedykh A et al. (2011) <doi:10.1289/ehp.1002476> and Sedykh A (2016) <doi:10.1007/978-1-4939-6346-1_14>). Other parametric fitting approaches (e.g., Hill equation) are also adopted for ease of comparison. 3-parameter Hill equation from tcpl package (Filer D et al., <doi:10.1093/bioinformatics/btw680>) and 4-parameter Hill equation from Curve Class2 approach (Wang Y et al., <doi:10.2174/1875397301004010057>) are available. Also, methods for calculating the confidence interval around the activity metrics are also provided. The methods are based on the bootstrap approach to simulate the datasets (Hsieh J-H et al. <doi:10.1093/toxsci/kfy258>). The simulated datasets can be used to derive the baseline noise threshold in an assay endpoint. This threshold is critical in the toxicological studies to derive the point-of-departure (POD).

Reversion mutations are secondary mutations that reverse the deleterious effects of an original pathogenic mutation, partially or fully restoring the gene's function. The revert package detects reversion mutations for a specific pathogenic mutation from DNA-seq bam files.

This web client interfaces Unpaywall <https://unpaywall.org/products/api>, formerly oaDOI, a service finding free full-texts of academic papers by linking DOIs with open access journals and repositories. It provides unified access to various data sources for open access full-text links including Crossref and the Directory of Open Access Journals (DOAJ). API usage is free and no registration is required.

This package implements Kornbrot's rank difference test as described in <doi:10.1111/j.2044-8317.1990.tb00939.x>. This method is a modified Wilcoxon signed-rank test which produces consistent and meaningful results for ordinal or monotonically-transformed data.

An R interface to Weka (Version 3.9.3). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars'. For more information on Weka see <https://www.cs.waikato.ac.nz/ml/weka/>.

This package provides methods and tools for Singular Spectrum Analysis including decomposition, forecasting and gap-filling for univariate and multivariate time series. General description of the methods with many examples can be found in the book Golyandina (2018, <doi:10.1007/978-3-662-57380-8>). See citation("Rssa") for details.

This package provides functions for linking and deduplicating data sets. Methods based on a stochastic approach are implemented as well as classification algorithms from the machine learning domain. For details, see our paper "The RecordLinkage Package: Detecting Errors in Data" Sariyar M / Borg A (2010) <doi:10.32614/RJ-2010-017>.

Robust tail dependence estimation for bivariate models. This package is based on two papers by the authors:'Robust and bias-corrected estimation of the coefficient of tail dependence and Robust and bias-corrected estimation of probabilities of extreme failure sets'. This work was supported by a research grant (VKR023480) from VILLUM FONDEN and an international project for scientific cooperation (PICS-6416).

This package provides helper functions for authenticating and retrieving data from your ODK-X Sync Endpoint'. This is an early release intended for testing and feedback.

PaleoClim <http://www.paleoclim.org> (Brown et al. 2019, <doi:10.1038/sdata.2018.254>) is a set of free, high resolution paleoclimate surfaces covering the whole globe. It includes data on surface temperature, precipitation and the standard bioclimatic variables commonly used in ecological modelling, derived from the HadCM3 general circulation model and downscaled to a spatial resolution of up to 2.5 minutes. Simulations are available for key time periods from the Late Holocene to mid-Pliocene. Data on current and Last Glacial Maximum climate is derived from CHELSA (Karger et al. 2017, <doi:10.1038/sdata.2017.122>) and reprocessed by PaleoClim to match their format; it is available at up to 30 seconds resolution. This package provides a simple interface for downloading PaleoClim data in R, with support for caching and filtering retrieved data by period, resolution, and geographic extent.

This package provides a thin wrapper around the tiktoken-rs crate, allowing to encode text into Byte-Pair-Encoding (BPE) tokens and decode tokens back to text. This is useful to understand how Large Language Models (LLMs) perceive text.

Allows work with Management API for load counters, segments, filters, user permissions and goals list from Yandex Metrica, Reporting API allows you to get information about the statistics of site visits and other data without using the web interface, Logs API allows to receive non-aggregated data and Compatible with Google Analytics Core Reporting API v3 allows receive information about site traffic and other data using field names from Google Analytics Core API. For more information see official documents <https://yandex.ru/dev/metrika/doc/api2/concept/about-docpage>.