Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

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shrinkem — by Joris Mulder, a month ago

Approximate Bayesian Regularization for Parsimonious Estimates

Approximate Bayesian regularization using Gaussian approximations. The input is a vector of estimates and a Gaussian error covariance matrix of the key parameters. Bayesian shrinkage is then applied to obtain parsimonious solutions. The method is described on Karimova, van Erp, Leenders, and Mulder (2025) . Gibbs samplers are used for model fitting. The shrinkage priors that are supported are Gaussian (ridge) priors, Laplace (lasso) priors (Park and Casella, 2008 ), and horseshoe priors (Carvalho, et al., 2010; ). These priors include an option for grouped regularization of different subsets of parameters (Meier et al., 2008; ). F priors are used for the penalty parameters lambda^2 (Mulder and Pericchi, 2018 ). This correspond to half-Cauchy priors on lambda (Carvalho, Polson, Scott, 2010 ).

popbayes — by Nicolas Casajus, 3 months ago

Bayesian Model to Estimate Population Trends from Counts Series

Infers the trends of one or several animal populations over time from series of counts. It does so by accounting for count precision (provided or inferred based on expert knowledge, e.g. guesstimates), smoothing the population rate of increase over time, and accounting for the maximum demographic potential of species. Inference is carried out in a Bayesian framework. This work is part of the FRB-CESAB working group AfroBioDrivers < https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/afrobiodrivers/>.

rnetcarto — by Daniel B. Stouffer, 3 years ago

Fast Network Modularity and Roles Computation by Simulated Annealing (Rgraph C Library Wrapper for R)

Provides functions to compute the modularity and modularity-related roles in networks. It is a wrapper around the rgraph library (Guimera & Amaral, 2005, ).

PINMA — by Hisashi Noma, 3 years ago

Improved Methods for Constructing Prediction Intervals for Network Meta-Analysis

Improved methods to construct prediction intervals for network meta-analysis. The parametric bootstrap and Kenward-Roger-type adjustment by Noma et al. (2022) are implementable.

MazamaSpatialUtils — by Jonathan Callahan, 2 years ago

Spatial Data Download and Utility Functions

A suite of conversion functions to create internally standardized spatial polygons data frames. Utility functions use these data sets to return values such as country, state, time zone, watershed, etc. associated with a set of longitude/latitude pairs. (They also make cool maps.)

googleAnalyticsR — by Erik Grönroos, 2 years ago

Google Analytics API into R

Interact with the Google Analytics APIs < https://developers.google.com/analytics/>, including the Core Reporting API (v3 and v4), Management API, User Activity API GA4's Data API and Admin API and Multi-Channel Funnel API.

RCarb — by Sebastian Kreutzer, 2 months ago

Dose Rate Modelling of Carbonate-Rich Samples

Translation of the 'MATLAB' program 'Carb' (Nathan and Mauz 2008 ; Mauz and Hoffmann 2014) for dose rate modelling for carbonate-rich samples in the context of trapped charged dating (e.g., luminescence dating) applications.

diario — by Andre Leite, 18 days ago

'R' Interface to the 'Diariodeobras' Application

Provides a set of functions for securely storing 'API' tokens and interacting with the < https://diariodeobras.net> system. Includes convenient wrappers around the 'httr2' package to perform authenticated requests, retrieve project details, tasks, reports, and more.

PSS.Health — by Rogério Boff Borges, 8 months ago

Power and Sample Size for Health Researchers via Shiny

Power and Sample Size for Health Researchers is a Shiny application that brings together a series of functions related to sample size and power calculations for common analysis in the healthcare field. There are functionalities to calculate the power, sample size to estimate or test hypotheses for means and proportions (including test for correlated groups, equivalence, non-inferiority and superiority), association, correlations coefficients, regression coefficients (linear, logistic, gamma, and Cox), linear mixed model, Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, limit of agreement on Bland-Altman plots, area under the curve, sensitivity and specificity incorporating the prevalence of disease. You can also use the online version at < https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/>.

highlightr — by Rachel Rogers, 2 months ago

Highlight Conserved Edits Across Versions of a Document

Input multiple versions of a source document, and receive HTML code for a highlighted version of the source document indicating the frequency of occurrence of phrases in the different versions. This method is described in Chapter 3 of Rogers (2024) < https://digitalcommons.unl.edu/dissertations/AAI31240449/>.