Selects one model with variable selection FDR controlled at a specified level. A q-value for each potential variable is also returned. The input, variable selection counts over many bootstraps for several levels of penalization, is modeled as coming from a beta-binomial mixture distribution.

Reproducibility is essential to the progress of research, yet achieving it remains elusive even in computational fields. Continuous Integration (CI) platforms offer a powerful way to launch automated workflows to check and document code, but often require considerable time, effort, and technical expertise to setup. We therefore developed the rworkflows suite to make robust CI workflows easy and freely accessible to all R package developers. rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, 2) an R package to quickly implement a standardised workflow, and 3) a centrally maintained GitHub Action.

Interface to JDemetra+ 3.x (<https://github.com/jdemetra>) time series analysis software. It offers full access to txt, csv, xml and spreadsheets files which are meant to be read by JDemetra+ Graphical User Interface.

Fast and efficient computation of rolling and expanding statistics for time-series data.

This package provides an interface to the Spotify API <https://developer.spotify.com/documentation/web-api/>.

R Markdown format for reveal.js presentations, a framework for easily creating beautiful presentations using HTML.

Some extensions to Rcmdr (R Commander), randomness test, variance test for one normal sample and predictions using active model, made by R-UCA project and used in teaching statistics at University of Cadiz (UCA).

This package provides classes and functions for modelling health care interventions using decision trees and semi-Markov models. Mechanisms are provided for associating an uncertainty distribution with each source variable and for ensuring transparency of the mathematical relationships between variables. The package terminology follows Briggs "Decision Modelling for Health Economic Evaluation" (2006, ISBN:978-0-19-852662-9).

Retime speech signals with a native Waveform Similarity Overlap-Add (WSOLA) implementation translated from the TSM toolbox by Driedger & Müller (2014) <https://www.audiolabs-erlangen.de/content/resources/MIR/TSMtoolbox/2014_DriedgerMueller_TSM-Toolbox_DAFX.pdf>. Design retimings and pitch (f0) transformations with tidy data and apply them via Praat interface. Produce spectrograms, spectra, and amplitude envelopes. Includes implementation of vocalic speech envelope analysis (fft_spectrum) technique and example data (mm1) from Tilsen, S., & Johnson, K. (2008) <doi:10.1121/1.2947626>.

An implementation of EDM algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with Rcpp wrappers around the cppEDM library. It implements the simplex projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the S-map algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, multiview embedding described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.

Seamless extraction of river networks from digital elevation models data. The package allows analysis of digital elevation models that can be either externally provided or downloaded from open source repositories (thus interfacing with the elevatr package). Extraction is performed via the D8 flow direction algorithm of TauDEM (Terrain Analysis Using Digital Elevation Models), thus interfacing with the traudem package. Resulting river networks are compatible with functions from the OCNet package. See Carraro (2023) <doi:10.5194/hess-27-3733-2023> for a presentation of the package.

This package provides comprehensive methods to measure disclosure risk and data utility for anonymized and synthetic data. Implements attribution-based risk metrics including Correct Attribution Probability (CAP), Targeted CAP (TCAP), Within Equivalence Class Attribution Probability (WEAP), and RAPID (Risk of Attribute Prediction-Induced Disclosure). Also provides distance-based privacy metrics such as Distance to Closest Record (DCR), Nearest Neighbor Distance Ratio (NNDR), and Identical Match Share (IMS). Utility assessment includes propensity score analysis, distribution comparisons, and various statistical tests. Methods are based on Taub et al. (2018) <doi:10.1007/978-3-319-99771-1_9> and related literature. Designed for integration with simPop S4 classes.

Computes 26 financial risk measures for any continuous distribution. The 26 financial risk measures include value at risk, expected shortfall due to Artzner et al. (1999) <DOI:10.1007/s10957-011-9968-2>, tail conditional median due to Kou et al. (2013) <DOI:10.1287/moor.1120.0577>, expectiles due to Newey and Powell (1987) <DOI:10.2307/1911031>, beyond value at risk due to Longin (2001) <DOI:10.3905/jod.2001.319161>, expected proportional shortfall due to Belzunce et al. (2012) <DOI:10.1016/j.insmatheco.2012.05.003>, elementary risk measure due to Ahmadi-Javid (2012) <DOI:10.1007/s10957-011-9968-2>, omega due to Shadwick and Keating (2002), sortino ratio due to Rollinger and Hoffman (2013), kappa due to Kaplan and Knowles (2004), Wang (1998)'s <DOI:10.1080/10920277.1998.10595708> risk measures, Stone (1973)'s <DOI:10.2307/2978638> risk measures, Luce (1980)'s <DOI:10.1007/BF00135033> risk measures, Sarin (1987)'s <DOI:10.1007/BF00126387> risk measures, Bronshtein and Kurelenkova (2009)'s risk measures.

Aims at loading Facebook and Instagram advertising data from Smartly.io into R. Smartly.io is an online advertising service that enables advertisers to display commercial ads on social media networks (see <http://www.smartly.io/> for more information). The package offers an interface to query the Smartly.io API and loads data directly into R for further data processing and data analysis.

Recursive partitioning methods to build classification trees for ordinal responses within the CART framework. Trees are grown using the Generalized Gini impurity function, where the misclassification costs are given by the absolute or squared differences in scores assigned to the categories of the response. Pruning is based on the total misclassification rate or on the total misclassification cost.

This package performs all steps in the credit scoring process. This package allows the user to follow all the necessary steps for building an effective scorecard. It provides the user functions for coarse binning of variables, Weights of Evidence (WOE) transformation, variable clustering, custom binning, visualization, and scaling of logistic regression coefficients. The results will generate a scorecard that can be used as an effective credit scoring tool to evaluate risk. For complete details on the credit scoring process, see Siddiqi (2005, ISBN:047175451X).

Mediation analysis for multiple mediators by penalized structural equation models with different types of penalties depending on whether there are multiple mediators and only one exposure and one outcome variable (using sparse group lasso) or multiple exposures, multiple mediators, and multiple outcome variables (using lasso, L1, penalties).

Reference-based multiple imputation of ordinal and binary responses under Bayesian framework, as described in Wang and Liu (2022) <arXiv:2203.02771>. Methods for missing-not-at-random include Jump-to-Reference (J2R), Copy Reference (CR), and Delta Adjustment which can generate tipping point analysis.

This package provides an interactive wrapper for the tmpinv() function from the rtmpinv package with options extending its functionality to pre- and post-estimation processing and streamlined incorporation of prior cell information. The Tabular Matrix Problems via Pseudoinverse Estimation (TMPinv) is a two-stage estimation method that reformulates structured table-based systems - such as allocation problems, transaction matrices, and input-output tables - as structured least-squares problems. Based on the Convex Least Squares Programming (CLSP) framework, TMPinv solves systems with row and column constraints, block structure, and optionally reduced dimensionality by (1) constructing a canonical constraint form and applying a pseudoinverse-based projection, followed by (2) a convex-programming refinement stage to improve fit, coherence, and regularization (e.g., via Lasso, Ridge, or Elastic Net).

Wrapper for the RSpace Electronic Lab Notebook (<https://www.researchspace.com/>) API. This packages provides convenience functions to browse, search, create, and edit your RSpace documents. In addition, it enables filling RSpace templates from R Markdown/Quarto templates or tabular data (e.g., Excel files). This R package is not developed or endorsed by Research Space'.

Data Envelopment Analysis for R, estimating robust DEA scores without and with environmental variables and doing returns-to-scale tests.

Randomization lists are an integral component of randomized clinical trials. randotools provides tools to easily create such lists.

This package provides methods for comparing different regression algorithms for describing the temporal dynamics of secondary tree growth (xylem and phloem). Users can compare the accuracy of the most common fitting methods usually used to analyse xylem and phloem data, i.e., Gompertz function, Double Gompertz function, General Additive Models (GAMs); and an algorithm newly introduced to the field, i.e., Bayesian Regularised Neural Networks (brnn). The core function of the package is XPSgrowth(), while the results can be interpreted using implemented generic S3 methods, such as plot() and summary().

Simulate samples from populations with known covariate distributions, generate response variables according to common linear and generalized linear model families, draw from sampling distributions of regression estimates, and perform visual inference on diagnostics from model fits.