Suite of utilities for accessing and manipulating data from the KoboToolbox API. KoboToolbox is a robust platform designed for field data collection in various disciplines. This package aims to simplify the process of fetching and handling data from the API. Detailed documentation for the KoboToolbox API can be found at <https://support.kobotoolbox.org/api.html>.

Simulation of several fractional and multifractional processes. Includes Brownian and fractional Brownian motions, bridges and Gaussian Haar-based multifractional processes (GHBMP). Implements the methods from Ayache, Olenko and Samarakoon (2025) <doi:10.48550/arXiv.2503.07286> for simulation of GHBMP. Estimation of Hurst functions and local fractal dimension. Clustering realisations based on the Hurst functions. Several functions to estimate and plot geometric statistics of the processes and time series. Provides a shiny application for interactive use of the functions from the package.

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).

Gene annotation of rice (Oryza Sativa L.spp.japonica). The package is based on the annotation file from the website <http://plants.ensembl.org/Oryza_sativa/Info/Index>. Input gene's name then return some information, including the from position, the end position, the position type and the chromosome number.

This package provides a RUT (Rol Unico Tributario) is an unique and personal identification number implemented in Chile to identify citizens and taxpayers. Rutifier allows to validate if a RUT exist or not and change between the different formats a RUT can have.

Utility functions to retrieve data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/help/costs-terms-and-conditions>). The package contains R wrappers to the UK NRFA data temporary-API. There are functions to retrieve stations falling in a bounding box, to generate a map and extracting time series and general information. The package is fully described in Vitolo et al (2016) "rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive" <https://journal.r-project.org/archive/2016/RJ-2016-036/RJ-2016-036.pdf>.

This package provides a modified implementation of stepwise regression that greedily searches the space of interactions among features in order to build polynomial regression models. Furthermore, the hypothesis tests conducted are valid-post model selection due to the use of a revisiting procedure that implements an alpha-investing rule. As a result, the set of rejected sequential hypotheses is proven to control the marginal false discover rate. When not searching for polynomials, the package provides a statistically valid algorithm to run and terminate stepwise regression. For more information, see Johnson, Stine, and Foster (2019) <arXiv:1510.06322>.

Population genetic data such as Single Nucleotide Polymorphisms (SNPs) is often used to identify genomic regions that have been under recent natural or artificial selection and might provide clues about the molecular mechanisms of adaptation. One approach, the concept of an Extended Haplotype Homozygosity (EHH), introduced by (Sabeti 2002) <doi:10.1038/nature01140>, has given rise to several statistics designed for whole genome scans. The package provides functions to compute three of these, namely: iHS (Voight 2006) <doi:10.1371/journal.pbio.0040072> for detecting positive or Darwinian selection within a single population as well as Rsb (Tang 2007) <doi:10.1371/journal.pbio.0050171> and XP-EHH (Sabeti 2007) <doi:10.1038/nature06250>, targeted at differential selection between two populations. Various plotting functions are included to facilitate visualization and interpretation of these statistics.

Build interactive Reliability Probability Plots with plotly by Carson Sievert (2020) <https://plotly.com/r/>, an interactive web-based graphing library.

Display a randomly selected quote about Richard M. Stallman based on the collection in the GNU Octave function fact() which was aggregated by Jordi Gutiérrez Hermoso based on the (now defunct) site stallmanfacts.com (which is accessible only via <http://archive.org>).

Implementation of Kernelized score functions and other semi-supervised learning algorithms for node label ranking to analyze biomolecular networks. RANKS can be easily applied to a large set of different relevant problems in computational biology, ranging from automatic protein function prediction, to gene disease prioritization and drug repositioning, and more in general to any bioinformatics problem that can be formalized as a node label ranking problem in a graph. The modular nature of the implementation allows to experiment with different score functions and kernels and to easily compare the results with baseline network-based methods such as label propagation and random walk algorithms, as well as to enlarge the algorithmic scheme by adding novel user-defined score functions and kernels.

Perform derivative-free optimization algorithms in R using C++. A wrapper interface is provided to call C function of the bobyqa implementation (See <https://github.com/emmt/Algorithms/tree/master/bobyqa>).

This tool enables the user to choose a randomization procedure based on sound scientific criteria. It comprises the generation of randomization sequences as well the assessment of randomization procedures based on carefully selected criteria. Furthermore, randomizeR provides a function for the comparison of randomization procedures.

We implement the algorithm estimating the parameters of the robust regression model with compositional covariates. The model simultaneously treats outliers and provides reliable parameter estimates. Publication reference: Mishra, A., Mueller, C.,(2019) <arXiv:1909.04990>.

Reads in text from unstructured modern Microsoft Office files (XML based files) such as Word and PowerPoint. This does not read in structured data (from Excel or Access) as there are many other great packages to that do so already.

Estimates life tables, specifically (crude) death rates and (raw and graduated) death probabilities, using rolling windows in one (e.g., age), two (e.g., age and time) or three (e.g., age, time and income) dimensions. The package can also be utilised for summarising statistics and smoothing continuous variables through rolling windows in other domains, such as estimating averages of self-positioning ideology in political science. Acknowledgements: The authors wish to thank Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Generalitat Valenciana (grants HIECPU/2023/2, Conselleria de Hacienda, Economà a y Administración Pública, and CIGE/2023/7, Conselleria de Educación, Cultura, Universidades y Empleo) for supporting this research.

This package implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The rdlearn package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.

Imports real-time thermo cycler (qPCR) data from Real-time PCR Data Markup Language (RDML) and transforms to the appropriate formats of the qpcR and chipPCR packages, as described in Rodiger et al. (2017) <doi:10.1093/bioinformatics/btx528>. Contains a dendrogram visualization for the structure of RDML object and GUI for RDML editing.

This package provides an Rcmdr plug-in based on the cpd package.

Use trend filtering, a type of regularized nonparametric regression, to estimate the instantaneous reproduction number, also called Rt. This value roughly says how many new infections will result from each new infection today. Values larger than 1 indicate that an epidemic is growing while those less than 1 indicate decline. For more details about this methodology, see Liu, Cai, Gustafson, and McDonald (2024) <doi:10.1371/journal.pcbi.1012324>.

This package provides an interface to many endpoints of Mixpanel's Data Export, Engage and JQL API. The R functions allow for event and profile data export as well as for segmentation, retention, funnel and addiction analysis. Results are always parsed into convenient R objects. Furthermore it is possible to load and update profiles.

Numerous functions for cohort-based analyses, either for prediction or causal inference. For causal inference, it includes Inverse Probability Weighting and G-computation for marginal estimation of an exposure effect when confounders are expected. We deal with binary outcomes, times-to-events, competing events, and multi-state data. For multistate data, semi-Markov model with interval censoring may be considered, and we propose the possibility to consider the excess of mortality related to the disease compared to reference lifetime tables. For predictive studies, we propose a set of functions to estimate time-dependent receiver operating characteristic (ROC) curves with the possible consideration of right-censoring times-to-events or the presence of confounders. Finally, several functions are available to assess time-dependent ROC curves or survival curves from aggregated data.

Wraps the Ollama <https://ollama.com> API, which can be used to communicate with generative large language models locally.

Computes revisitation metrics for trajectory data, such as the number of revisitations for each location as well as the time spent for that visit and the time since the previous visit. Also includes functions to plot data.