This package provides a Shiny application to access the functionalities and datasets of the archeofrag package for spatial analysis in archaeology from refitting data. Quick and seamless exploration of archaeological refitting datasets, focusing on physical refits only. Features include: built-in documentation and convenient workflow, plot generation and exports, exploration of spatial units merging solutions, simulation of archaeological site formation processes, support for parallel computing, R code generation to re-execute simulations and ensure reproducibility, code generation for the openMOLE model exploration software. A demonstration of the app is available at <https://analytics.huma-num.fr/Sebastien.Plutniak/archeofrag/>.

When many possible multiplier method estimates of a target population are available, a weighted sum of estimates from each back-calculated path can be achieved with this package. Variance-minimizing weights are used and with any admissible tree-structured data. The methodological basis used to create this package can be found in Flynn (2023) <http://hdl.handle.net/2429/86174>.

Compute approach bias scores using different scoring algorithms, compute bootstrapped and exact split-half reliability estimates, and compute confidence intervals for individual participant scores.

Causal discovery in linear structural equation models (Schultheiss, and Bühlmann (2023) <doi:10.1093/biomet/asad008>) and vector autoregressive models (Schultheiss, Ulmer, and Bühlmann (2025) <doi:10.1515/jci-2024-0011>) with explicit error control for false discovery, at least asymptotically.

Annuity Random Interest Rates proposes different techniques for the approximation of the present and final value of a unitary annuity-due or annuity-immediate considering interest rate as a random variable. Cruz Rambaud et al. (2017) <doi:10.1007/978-3-319-54819-7_16>. Cruz Rambaud et al. (2015) <doi:10.23755/rm.v28i1.25>.

This package provides several methods for aggregating probabilistic forecasts. You have a group of people who have made probabilistic forecasts for the same event. You want to take advantage of the "wisdom of the crowd" and combine these forecasts in some sensible way. This package provides implementations of several strategies, including geometric mean of odds, an extremized aggregate (Neyman, Roughgarden (2021) <doi:10.1145/3490486.3538243>), and "high-density trimmed mean" (Powell et al. (2022) <doi:10.1037/dec0000191>).

Create American Psychological Association Style, Seventh Edition documents. Format numbers and text consistent with APA style. Create tables that comply with APA style by extending flextable functions.

Set of functions to create clear graphics and run common statistical analyses for agricultural experiments (ANOVA with post-hoc tests such as Tukey HSD and Duncan MRR, coefficient of variation, and simple power calculations), streamlining exploratory analysis and reporting. Functions build on ggplot2 and base stats and follow methods widely used in agronomy (field trials, plant breeding). Key references include Tukey (1949) <doi:10.2307/3001913>, Duncan (1955) <doi:10.2307/3001478>, Cohen (1988, ISBN:9781138892899); see also agricolae <https://CRAN.R-project.org/package=agricolae> and Wickham (2016, ISBN:9783319242750) for ggplot2'. Versión en español: Conjunto de funciones para generar gráficos claros y ejecutar análisis habituales en ensayos agrà colas (ANOVA con pruebas post-hoc como Tukey HSD y Duncan MRR, coeficiente de variación y cálculos simples de potencia), facilitando el análisis exploratorio y la elaboración de reportes. Los métodos implementados se basan en Tukey (1949) <doi:10.2307/3001913>, Duncan (1955) <doi:10.2307/3001478> y Cohen (1988, ISBN:9781138892899); ver también agricolae <https://CRAN.R-project.org/package=agricolae> y Wickham (2016, ISBN:9783319242750) para ggplot2'.

This package provides a decision support tool to strategically prioritise evidence gathering in complex, hierarchical AND-OR decision trees. It is designed for situations with incomplete or uncertain information where the goal is to reach a confident conclusion as efficiently as possible (responding to the minimum number of questions, and only spending resources on generating improved evidence when it is of significant value to the final decision). The framework excels in complex analyses with multiple potential successful pathways to a conclusion ('OR nodes). Key features include a dynamic influence index to guide users to the most impactful question, a system for propagating answers and semi-quantitative confidence scores (0-5) up the tree, and post-conclusion guidance to identify the best actions to increase the final confidence. These components are brought together in an interactive command-line workflow that guides the analysis from start to finish.

This package contains data and functions that can be used to make actuarial life tables. Each function adds a column to the inputted dataset for each intermediate calculation between mortality rate and life expectancy. Users can run any of our functions to complete the life table until that step, or run lifetable() to output a full life table that can be customized to remove optional columns. Methods for creating lifetables are as described in Zedstatistics (2021) <https://www.youtube.com/watch?v=Dfe59glNXAQ>.

The Aquo Standard is the Dutch Standard for the exchange of data in water management. With *aquodom* (short for aquo domaintables) it is easy to exploit the API (<https://www.aquo.nl/index.php/Hoofdpagina>) to download domaintables of the Aquo Standard and use them in R.

We curated 147 of expression array, from 3 species(human,mouse,rat), 3 companies('Affymetrix','Illumina','Agilent'), by aligning the Fasta sequences of all probes of each platform to their corresponding reference genome, and then annotate them to genes.

The tools in this package are intended to help researchers assess multiple treatment-covariate interactions with data from a parallel-group randomized controlled clinical trial. The methods implemented in the package were proposed in Kovalchik, Varadhan and Weiss (2013) <doi: 10.1002/sim.5881>.

Estimates and plots effect estimates from models with all possible combinations of a list of variables. It can be used for assessing treatment effects in clinical trials or risk factors in bio-medical and epidemiological research. Like Stata command confall (Wang Z (2007) <doi:10.1177/1536867X0700700203> ), allestimates calculates and stores all effect estimates, and plots them against p values or Akaike information criterion (AIC) values. It currently has functions for linear regression: all_lm(), logistic and Poisson regression: all_glm(), and Cox proportional hazards regression: all_cox().

This package provides a developer-facing interface to the Arrow Database Connectivity ('ADBC') PostgreSQL driver for the purposes of building high-level database interfaces for users. ADBC <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses Arrow for result sets and query parameters.

Estimates a first-price auction model with conditionally independent private values as described in MacKay (2020) <doi:10.2139/ssrn.3096534>. The model allows for unobserved heterogeneity that is common to all bidders in addition to observable heterogeneity.

This package implements adaptive tau leaping to approximate the trajectory of a continuous-time stochastic process as described by Cao et al. (2007) The Journal of Chemical Physics <doi:10.1063/1.2745299> (aka. the Gillespie stochastic simulation algorithm). This package is based upon work supported by NSF DBI-0906041 and NIH K99-GM104158 to Philip Johnson and NIH R01-AI049334 to Rustom Antia.

The Langmuir and Freundlich adsorption isotherms are pivotal in characterizing adsorption processes, essential across various scientific disciplines. Proper interpretation of adsorption isotherms involves robust fitting of data to the models, accurate estimation of parameters, and efficiency evaluation of the models, both in linear and non-linear forms. For researchers and practitioners in the fields of chemistry, environmental science, soil science, and engineering, a comprehensive package that satisfies all these requirements would be ideal for accurate and efficient analysis of adsorption data, precise model selection and validation for rigorous scientific inquiry and real-world applications. Details can be found in Langmuir (1918) <doi:10.1021/ja02242a004> and Giles (1973) <doi:10.1111/j.1478-4408.1973.tb03158.x>.

It provides the density, distribution function, quantile function, random number generator, likelihood function, moments and Maximum Likelihood estimators for a given sample, all this for the three parameter Asymmetric Laplace Distribution defined in Koenker and Machado (1999). This is a special case of the skewed family of distributions available in Galarza et.al. (2017) <doi:10.1002/sta4.140> useful for quantile regression.

This package provides a collection of model checking methods for semiparametric accelerated failure time (AFT) models under the rank-based approach. For the (computational) efficiency, Gehan's weight is used. It provides functions to verify whether the observed data fit the specific model assumptions such as a functional form of each covariate, a link function, and an omnibus test. The p-value offered in this package is based on the Kolmogorov-type supremum test and the variance of the proposed test statistics is estimated through the re-sampling method. Furthermore, a graphical technique to compare the shape of the observed residual to a number of the approximated realizations is provided. See the following references; A general model-checking procedure for semiparametric accelerated failure time models, Statistics and Computing, 34 (3), 117 <doi:10.1007/s11222-024-10431-7>; Diagnostics for semiparametric accelerated failure time models with R package afttest', arXiv, <doi:10.48550/arXiv.2511.09823>.

Sample of hydro-meteorological datasets extracted from the CAMELS-FR French database <doi:10.57745/WH7FJR>. It provides metadata and catchment-scale aggregated hydro-meteorological time series on a pool of French catchments for use by the airGR packages.

The aligned rank transform for nonparametric factorial ANOVAs as described by Wobbrock, Findlater, Gergle, and Higgins (2011) <doi:10.1145/1978942.1978963>. Also supports aligned rank transform contrasts as described by Elkin, Kay, Higgins, and Wobbrock (2021) <doi:10.1145/3472749.3474784>.

Modern software often poorly support older file formats. This package intends to handle many file formats that were native to the antiquated Commodore Amiga machine. This package focuses on file types from the older Amiga operating systems (<= 3.0). It will read and write specific file formats and coerces them into more contemporary data.

Estimate the AUC using a variety of methods as follows: (1) frequentist nonparametric methods based on the Mann-Whitney statistic or kernel methods. (2) frequentist parametric methods using the likelihood ratio test based on higher-order asymptotic results, the signed log-likelihood ratio test, the Wald test, or the approximate t solution to the Behrens-Fisher problem. (3) Bayesian parametric MCMC methods.