R

R

A mirror of https://git.sr.ht/~enricoschumann/PMwR

An R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with antibiotic data by using evidence-based methods.

Ansible collection for Data Science related tools

https://galaxy.ansible.com/ui/repo/published/devxy/data_science_core/

Fit parametric models for time-to-event data that show an initial 'incubation period', i.e., a variable phase where the hazard is zero. The delayed Weibull distribution serves as the foundational data model. The specific method of MPSE (maximum product of spacings estimation) or different variants of MLE (maximum likelihood estimation) are implemented for parameter estimation. Bootstrap confidence intervals for parameters and significance tests in a two group setting are provided as well.

Mirrored to https://gitlab.b-data.ch/r/rsi and https://github.com/b-data/rsi.

R package to create an interaction matrix from DPSIR variables, and to create a survey on KoboToolbox to ask for how variables affect each other.

Helm chart for Shinyproxy

Materials and resources for the teaching unit "Morphometrics with R" (University of Bordeaux, Summer School, 2024). Website.

Ansible collection for Posit applications

https://galaxy.ansible.com/ui/repo/published/devxy/posit/

This project investigates the impact of Forest Protected Area (FPA) designations on deforestation in the South American Atlantic Forest region, which spans Argentina, Brazil, and Paraguay. Leveraging remote-sensed forest cover data from 2000 to 2020 and geo-referenced socio-economic variables, the analysis applies a pseudo-randomized design to evaluate how FPA status influences forest loss. Results indicate that FPA designation reduced the odds of deforestation by approximately 14%, with protected areas exhibiting significantly lower deforestation rates (~5%) compared to non-protected forests (~19%). This effect size surpasses previous estimates from other Latin American regions, underscoring the critical role of conservation policy in this biodiversity hotspot. The project provides a reproducible framework for assessing FPA effectiveness and sets the stage for future research on the socio-economic impacts of forest conservation.

This project supports a spatial analysis of deforestation trends and drivers in the tri-national Paraná Atlantic Forest region, as presented in Mohebalian et al. (2022). Using geospatial data from Argentina, Brazil, and Paraguay, the study quantifies forest loss between 2000 and 2020 and evaluates the influence of factors such as road proximity, urban access, economic growth, and population density. The project uses statistical modeling and spatial data tools in R to estimate the effectiveness of Forest Protected Areas (FPAs) in mitigating deforestation. Results show heterogeneous policy impacts across countries, providing valuable insights for cross-border conservation planning and forest governance.

Probability and Statistics A regression model for predicting how patients will rate their pain in 12 months.

Documentos referentes al curso de Introducción a la bioestadística y programación:

Hojas de cálculo Bioestadística Programas bioinformáticos Bases de datos biosanitarias Lenguajes de programación Lenguaje de programación R

A repository for the Workshop course on Data Analytics using spreadsheets and R for MIEMP.

CC by SA 4.0

Estimate of personal CO2 footprint based on records of vehicle mileage, household energy consumption and air travel emissions

Containerfiles for R

R script providing an estimate of the probability of obtaining a bib as a function of the number of Running Stones and the number of years entered in the lottery for UTMB final.

Draft for a medium online course (moc) on using R for data analysis in the psychological sciences and related fields

repo de publication sur le parc locatif social

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