A collection of helper functions for some common tasks in fitting linear models, mainly by lm().
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Updated
Feb 19, 2025 - R
A collection of helper functions for some common tasks in fitting linear models, mainly by lm().
Presentation-Ready Data Summary and Analytic Result Tables
Bootstrap p-values, including convenience functions for regression models.
🌌 The R easystats-project
📊 Computation and processing of models' parameters
Regression model building and forecasting in R
R package for fitting joint models to time-to-event data and multivariate longitudinal data
Enhancing {ggplot2} plots with statistical analysis 📊📣
How does the rise of carbon dioxide emissions affect agricultural production from over 60 countries? Interested in the relationship between CO2 emissions, renewable energy usage, and agricultural emission factor on short-term production.
R Package for Quantile Recalibration of Gaussian Models
Files associated with team-level statistics analysis and prediction of goals outcome of football teams.
Dynamic Modeling and Machine Learning Environment
An R package for obtaining nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers or splines
How does type of major airport and year of flight affect flight path demand? Interested in the relationship between the COVID-19 pandemic and demand for certain flight paths.
Fitting an exchangeable 2-copule model
Statistical Multiple Linear Regression model built in R Programming Language to predict the next day Maximum and Minimum Temperature
Knights et al. (2025). Neural Evidence of Functional Compensation for Fluid Intelligence in Healthy Ageing. eLife.
Aplicação do Algoritmo proposto em https://doi.org/10.1214/21-BA1294 em misturas de regressão t de Student assimétricas.
An R implementation of a new covariates selection method in Dynamic Regression Models.
Une analyse de la criminalité en fonction de variables socio-économiques a été menée, incluant la sélection et la comparaison de modèles de régression multiple ainsi que des tests d'hypothèses sur les coefficients et la significativité des modèles.
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