Simulate the dynamic of lion populations using a specific Individual-Based Model (IBM) compiled in C.

This package provides a quadratic time dynamic programming algorithm can be used to compute an approximate solution to the problem of finding the most likely changepoints with respect to the Poisson likelihood, subject to a constraint on the number of segments, and the changes which must alternate: up, down, up, down, etc. For more info read <http://proceedings.mlr.press/v37/hocking15.html> "PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data" by TD Hocking et al, proceedings of ICML2015.

Run Queries against the API of Piwik Pro <https://developers.piwik.pro/en/latest/custom_reports/http_api/http_api.html>. The result is a tibble.

Includes functions for keyword search of pdf files. There is also a wrapper that includes searching of all files within a single directory.

Implementation of penalized regression with second-generation p-values for variable selection. The algorithm can handle linear regression, GLM, and Cox regression. S3 methods print(), summary(), coef(), predict(), and plot() are available for the algorithm. Technical details can be found at Zuo et al. (2021) <doi:10.1080/00031305.2021.1946150>.

This package provides a framework for creating interactive figures for data exploration. All plots are automatically linked and support several kinds of interactive features, including selection, zooming, panning, and parameter manipulation. The figures can be interacted with either manually, using a mouse and a keyboard, or by running code from inside an active R session.

Exports an enhanced version of the tools::parseLatex() function to handle LaTeX syntax more accurately. Also includes numerous functions for searching and modifying LaTeX source.

Analytical power calculations for GxE and GxG interactions for case-control studies of candidate genes and genome-wide association studies (GWAS). This includes power calculation for four two-step screening and testing procedures. It can also calculate power for GxE and GxG without any screening.

Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots. See Chapter 8 (Portfolio Backtesting) of the book: Daniel P. Palomar, "Portfolio Optimization: Theory and Application", Cambridge University Press, 2025.

Scored responses and responses times from the Canadian subsample of the PISA 2018 assessment, accessible as the "Cognitive items total time/visits data file" by OECD (2020) <https://www.oecd.org/pisa/data/2018database/>.

Fits the Poisson-Tweedie generalized linear mixed model described in Signorelli et al. (2021, <doi:10.1177/1471082X20936017>). Likelihood approximation based on adaptive Gauss Hermite quadrature rule.

An implementation of the ternary plot for interpreting regression coefficients of trinomial regression models, as proposed in Santi, Dickson and Espa (2019) <doi:10.1080/00031305.2018.1442368>. Ternary plots can be drawn using either ggtern package (based on ggplot2') or Ternary package (based on standard graphics). The package and its features are illustrated in Santi, Dickson, Espa and Giuliani (2022) <doi:10.18637/jss.v103.c01>.

This package provides programmatic access to GitHub API with a focus on project management. Key functionality includes setting up issues and milestones from R objects or YAML configurations, querying outstanding or completed tasks, and generating progress updates in tables, charts, and RMarkdown reports. Useful for those using GitHub in personal, professional, or academic settings with an emphasis on streamlining the workflow of data analysis projects.

This package provides a collection of utilities and ggplot2 extensions to assist with visualisations in genomic epidemiology. This includes the phylepic chart, a visual combination of a phylogenetic tree and a matched epidemic curve. The included ggplot2 extensions such as date axes binned by week are relevant for other applications in epidemiology and beyond. The approach is described in Suster et al. (2024) <doi:10.1101/2024.04.02.24305229>.

Returns almost all features that has been extracted from Position Specific Scoring Matrix (PSSM) so far, which is a matrix of L rows (L is protein length) and 20 columns produced by PSI-BLAST which is a program to produce PSSM Matrix from multiple sequence alignment of proteins see <https://www.ncbi.nlm.nih.gov/books/NBK2590/> for mor details. some of these features are described in Zahiri, J., et al.(2013) <DOI:10.1016/j.ygeno.2013.05.006>, Saini, H., et al.(2016) <DOI:10.17706/jsw.11.8.756-767>, Ding, S., et al.(2014) <DOI:10.1016/j.biochi.2013.09.013>, Cheng, C.W., et al.(2008) <DOI:10.1186/1471-2105-9-S12-S6>, Juan, E.Y., et al.(2009) <DOI:10.1109/CISIS.2009.194>.

Implementations of Power Fuzzy Clustering (PFC) and Power Fuzzy Cluster-wise Regression (PFCR) for multivariate data. The package supports Minkowski distances, with the L1 case solved via iteratively re-weighted least squares and the case p > 1 solved via coordinate-wise root finding, as well as an adaptive, regularised Mahalanobis distance with per-cluster covariance matrices. Both plain fuzzy clustering and cluster-wise linear regression are provided. The corresponding paper can be found at Nguyen P.T., Tortora C., and Punzo A. (2026) <doi:10.1109/TFUZZ.2026.3683998>.

Mixtures of Poisson Generalized Linear Models for high dimensional count data clustering. The (multivariate) responses can be partitioned into set of blocks. Three different parameterizations of the linear predictor are considered. The models are estimated according to the EM algorithm with an efficient initialization scheme <doi:10.1016/j.csda.2014.07.005>.

Reproducible, programmatic retrieval of survey datasets from the Pew Research Center.

Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahuan desert. The raw data files can be found at <https://github.com/weecology/portaldata>.

This package provides a set of modular, pipeable functions to calculate PageRank scores from edge lists and redirect reports, common in SEO analysis. Functions handle URL cleaning, redirect resolution, edge deduplication, isolate handling, and PageRank computation using base R for data manipulation and igraph for core PageRank calculation.

This package provides a lightweight message system relying purely on base R. Comes with built-in and pre styled message types and provides an easy way to create custom messages. Supports individually styled and colored text as well as timing information. Designed to make console output more informative and visually organized.

Identifies differences between versions of a package. Specifically, the functions help determine if there are breaking changes from one package version to the next. The package also includes a stability assessment, to help you determine the overall stability of a package, or even an entire repository.

This package provides wrapper functions to access the ProPublica's Congress and Campaign Finance APIs. The Congress API provides near real-time access to legislative data from the House of Representatives, the Senate and the Library of Congress. The Campaign Finance API provides data from United States Federal Election Commission filings and other sources. The API covers summary information for candidates and committees, as well as certain types of itemized data. For more information about these APIs go to: <https://www.propublica.org/datastore/apis>.

Functional claims reserving methods based on aggregated chain-ladder data, also known as a run-off triangle, implemented in three nonparametric algorithms (PARALLAX, REACT, and MACRAME) proposed in Maciak, Mizera, and Pešta (2022) <doi:10.1017/asb.2022.4>. Additional methods including permutation bootstrap for completed run-off triangles are also provided.