Collection of R scripts for reproducible data analysis

This release includes updates and additions to the R scripts repository for reproducible data analysis.

Release notes (v1.0.2)

This release includes updates and additions to the R scripts repository for reproducible data analysis. Changes in this version include:

New scripts added

• XGBoost_linear regression_nested CV.R: Extreme Gradient Boosting (XGBoost) for linear regression with nested cross-validation.

• XGBoost_ordinal logistic classification.R: XGBoost for logistic ordinal regression with nested cross-validation.

• Multi-class XGBoost.R: multi-class prediction using XGBoost.

• Continuous_Multioutput_XGBoost.R: generalizable R and Python workflow for continuous multi-output regression using XGBoost.

• Linear BMA.R: Bayesian Model Averaging (BMA) analysis for probabilistic model selection in linear regression.

• SHAP_direction.R: function for determining feature direction based on SHAP values using Rcpp pairwise counting.

• BKMR.R: Bayesian kernel machine regression (BKMR) analysis.

• WQS.R: weighted quantile sum regression (WQS) analysis.

• PSM.R: propensity score matching (PSM) analysis.

• RCS.R: restricted cubic spline (RCS) analysis.

• Convert_semi transparent color to opaque.R: function to convert a semi-transparent color to its opaque equivalent, considering the visual effect on a white background.

• Loading and using a model.R: function for loading a saved model and make new prediction.

• Carbon_footprint.R: function attempting to estimate energy consumption and carbon emissions from running R code.

Updated scripts

• Logistic BMA.R: added example dataset for reproducibility.

• Survival XGBoost Cox analysis.R: added example dataset for reproducibility.

• XGBoost_binary classification_nested CV.R: added example dataset for reproducibility.

Usage notes

• All scripts are documented with instructions and, where applicable, example datasets.

• Ensure the required R packages are installed: xgboost, BMA, survival, etc.

Version notes

• This release is version v1.0.2.

• For reproducibility, cite the DOI of this release when using these scripts.

All previously released scripts are included unchanged in this version.

Collection of R scripts for reproducible data analysis

This release includes updates and additions to the R scripts repository for reproducible data analysis.
Changes in this version include:

New scripts added
• Logistic_BMA_script.R: Logistic Bayesian Model Averaging (BMA) analysis for probabilistic model selection in logistic regression.
• XGBoost_binary classification_nested CV.R: Extreme Gradient Boosting (XGBoost) for binary classification with nested cross-validation.

Usage notes
• All scripts are documented with instructions and, where applicable, example datasets.
• Ensure the required R packages are installed: xgboost, BMA, survival, etc.

Version notes
• This release is version v1.0.1
• For reproducibility, cite the DOI of this release when using these scripts.

All previously released scripts are included unchanged in this version.

Collection of R scripts for reproducible data analysis

This release provides a collection of R scripts for reproducible data analysis in scientific research. The scripts include:
• Extreme Gradient Boosting (XGBoost) adapted for Cox proportional hazards modeling – for survival analysis.

All scripts are documented with usage instructions and, where applicable, example datasets to facilitate reproducibility.

Requirements
• R (version ≥ 4.0.0)
• Required packages: xgboost, BMA, survival, and other dependencies listed in each script.

Notes
• This is the initial release of the repository.
• Users are encouraged to cite this DOI when using any of the scripts in publications.