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.

R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.

Recursive algorithms for computing various relatedness coefficients, including pairwise kinship, kappa and identity coefficients. Both autosomal and X-linked coefficients are computed. Founders are allowed to be inbred, which enables construction of any given kappa coefficients, as described in Vigeland (2020) <doi:10.1007/s00285-020-01505-x>. In addition to the standard coefficients, ribd also computes a range of lesser-known coefficients, including generalised kinship coefficients, multi-person coefficients and two-locus coefficients (Vigeland, 2023, <doi:10.1093/g3journal/jkac326>). Many features of ribd are available through the online app QuickPed at <https://magnusdv.shinyapps.io/quickped>; see Vigeland (2022) <doi:10.1186/s12859-022-04759-y>.

Conducts mediation analysis for structural equation models (SEM) estimated with lavaan', blavaan', cSEM', or modsem'. Implements the Baron and Kenny (1986) <doi:10.1037/0022-3514.51.6.1173> and Zhao, Lynch & Chen (2010) <doi:10.1086/651257> approaches to determine the presence and type of mediation. Supports covariance-based SEM, partial least squares SEM, Bayesian SEM, and moderated mediation and mediated moderation models. Tests indirect effects with the Sobel, Delta, Monte-Carlo, and bootstrap methods or, for Bayesian models, with posterior summaries and equal-tailed or highest density credible intervals. Reports the effect size measures RIT, RID, and Upsilon of Lachowicz, Preacher and Kelley (2018) <doi:10.1037/met0000165>. Results can be summarized, extracted with standard methods such as summary(), coef() and confint(), and plotted.

Enhances the R Optimization Infrastructure ('ROI') package with the quadratic solver qpOASES'. More information about qpOASES can be found at <https://github.com/coin-or/qpOASES>.

An implementation to compute an optimal dose escalation rule using deep reinforcement learning in phase I oncology trials (Matsuura et al. (2023) <doi:10.1080/10543406.2023.2170402>). The dose escalation rule can directly optimize the percentages of correct selection (PCS) of the maximum tolerated dose (MTD).

Compute the values of various parameters evaluating how similar two multidimensional datasets structures are in multidimensional space, as described in: Jouan-Rimbaud, D., Massart, D. L., Saby, C. A., Puel, C. (1998), <doi:10.1016/S0169-7439(98)00005-7>. The computed parameters evaluate three properties, namely, the direction of the data sets, the variance-covariance of the data points, and the location of the data sets centroids. The package contains workhorse function jrparams(), as well as two helper functions Mboxtest() and JRsMahaldist(), and four example data sets.

This package provides an efficient procedure for fitting the entire solution path for high-dimensional regularized quadratic generalized linear models with interactions effects under the strong or weak heredity constraint.

Perform risk-adjusted regression and sensitivity analysis as developed in "Mitigating Omitted- and Included-Variable Bias in Estimates of Disparate Impact" Jung et al. (2024) <arXiv:1809.05651>.

Functionality to download stock prices, cryptocurrency data, and more from the Tiingo API <https://api.tiingo.com/>.

Researchers commonly need to summarize scientific information, a process known as evidence synthesis'. The first stage of a synthesis process (such as a systematic review or meta-analysis) is to download a list of references from academic search engines such as Web of Knowledge or Scopus'. The traditional approach to systematic review is then to sort these data manually, first by locating and removing duplicated entries, and then screening to remove irrelevant content by viewing titles and abstracts (in that order). revtools provides interfaces for each of these tasks. An alternative approach, however, is to draw on tools from machine learning to visualise patterns in the corpus. In this case, you can use revtools to render ordinations of text drawn from article titles, keywords and abstracts, and interactively select or exclude individual references, words or topics.

Various functions for querying and reshaping dependency trees, as for instance created with the spacyr or udpipe packages. This enables the automatic extraction of useful semantic relations from texts, such as quotes (who said what) and clauses (who did what). Method proposed in Van Atteveldt et al. (2017) <doi:10.1017/pan.2016.12>.

Datasets and utilities for teaching linear models in the context of the BetaBit universe (StatPunk). The package provides simulated datasets based on the fictional LifeCalc algorithmic scoring system, illustrating concepts such as simple regression, ANOVA, ANCOVA, hierarchical models, multicollinearity, model selection (AIC, BIC), and regularisation (LASSO, Ridge). Each dataset is accompanied by a narrative context connecting statistical methodology to questions of algorithmic fairness and social consequence.

Calculate RNNI distance between and manipulate with ranked trees. RNNI stands for Ranked Nearest Neighbour Interchange and is an extension of the classical NNI space (space of trees created by the NNI moves) to ranked trees, where internal nodes are ordered according to their heights (usually assumed to be times). The RNNI distance takes the tree topology into account, as standard NNI does, but also penalizes changes in the order of internal nodes, i.e. changes in the order of times of evolutionary events. For more information about the RNNI space see: Gavryushkin et al. (2018) <doi:10.1007/s00285-017-1167-9>, Collienne & Gavryushkin (2021) <doi:10.1007/s00285-021-01567-5>, Collienne et al. (2021) <doi:10.1007/s00285-021-01685-0>, and Collienne (2021) <http://hdl.handle.net/10523/12606>.

Collects published kinetics of ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) and uses these kinetics to model the carboxylation rate across CO2 and O2 concentrations and different temperatures. The carboxylation rate can be modeled as the gross rate or the net rate, which takes into account the oxygenase activity of the enzyme using one of the three known phosphoglycolate salvage pathways. Custom enzymes and temperature dependences can be created with user kinetics, or published kinetics can be accessed through a meta-analysis contained within the package. An expansion of methods from Harrison et al. (2025) <doi:10.1128/aem.00604-25>.

Scelestial infers a lineage tree from single-cell DNA mutation matrix. It generates a tree with approximately maximum parsimony through a Steiner tree approximation algorithm.

This package provides tools for getting historical weather information and forecasts from wunderground.com. Historical weather and forecast data includes, but is not limited to, temperature, humidity, windchill, wind speed, dew point, heat index. Additionally, the weather underground weather API also includes information on sunrise/sunset, tidal conditions, satellite/webcam imagery, weather alerts, hurricane alerts and historical high/low temperatures.

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>.

Quantitative Structure-Activity Relationship (QSAR) modeling is a valuable tool in computational chemistry and drug design, where it aims to predict the activity or property of chemical compounds based on their molecular structure. In this vignette, we present the rQSAR package, which provides functions for variable selection and QSAR modeling using Multiple Linear Regression (MLR), Partial Least Squares (PLS), and Random Forest algorithms.

Understanding heterogeneous causal effects based on pretreatment covariates is a crucial step in modern empirical work in data science. Building on the recent developments in Calonico et al (2025) <doi:10.48550/arXiv.2503.13696>, this package provides tools for estimation and inference of heterogeneous treatment effects in Regression Discontinuity (RD) Designs. The package includes two main commands: rdhte to conduct estimation and robust bias-corrected inference for conditional RD treatment effects (given choice of bandwidth parameter); rdbwhte', which implements automatic bandwidth selection methods; and rdhte_lincom to test linear combinations of parameters.

This package contains various tools to estimate, analyze, and visualize Response Item Networks. ResIN dummy-codes ordered and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.

Rossby wave ray paths are traced from a determined source, specified wavenumber, and direction of propagation. "raytracing" also works with a set of experiments changing these parameters, making possible the identification of Rossby wave sources automatically. The theory used here is based on classical studies, such as Hoskins and Karoly (1981) <doi:10.1175/1520-0469(1981)038%3C1179:TSLROA%3E2.0.CO;2>, Karoly (1983) <doi:10.1016/0377-0265(83)90013-1>, Hoskins and Ambrizzi (1993) <doi:10.1175/1520-0469(1993)050%3C1661:RWPOAR%3E2.0.CO;2>, and Yang and Hoskins (1996) <doi:10.1175/1520-0469(1996)053%3C2365:PORWON%3E2.0.CO;2>.

An RStudio addin providing a visual, point-and-click interface for data manipulation and analysis, designed for users transitioning from SPSS to R. Every visual action generates clean, reproducible R code using tidyverse conventions ('dplyr', tidyr'). Includes a context-aware AI copilot supporting multiple LLM providers ('OpenAI', Anthropic Claude, Google Gemini') with built-in proxy support and privacy controls.

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