Software

๐Ÿ“ฆ Software/Packages

This page provides links to R packages I have (co)authored. The most recent versions of most packages are on github. Most R packages are also available on CRAN.


๐Ÿ“š R Packages / Software


๐Ÿ“Š ICsurv

ICsurv: Semiparametric Regression Analysis of Interval-Censored Data
๐Ÿ”— CRAN Page
๐Ÿ“ An R package for semiparametric regression analysis of interval-censored data, providing robust statistical tools for handling censored data in various applications.


๐Ÿ” aenetgt

aenetgt: Adaptive Elastic Net for Group Testing
๐Ÿ”— GitHub Repository
๐Ÿ“ Software for implementing adaptive elastic net regression for group testing, optimizing variable selection in pooled testing data analyses.


๐Ÿ“ˆ GAM

GAM: Generalized Additive Regression for Group Testing Data
๐Ÿ”— GitHub Repository
๐Ÿ“ Software for applying generalized additive regression to group testing data, providing flexible modeling for pooled testing analyses.


๏ฟฝ JMTB

JMTB: Bayesian Regression Model for Group Testing Data
๐Ÿ”— GitHub Repository
๐Ÿ“ Implements a Bayesian regression model with spike and slab variable selection for group testing data.


๐Ÿงช Group-Testing

Group-Testing: Dilution Effect in Group Testing Regression
๐Ÿ”— GitHub Repository
๐Ÿ“ Novel approach for acknowledging the dilution effect in group testing regression.


๐Ÿ“ฆ binGroup2

binGroup2: R Package for Group Testing
๐Ÿ”— CRAN Page
๐Ÿ“ Provides statistical tools for group testing analysis in infectious disease surveillance.


๐Ÿ› ๏ธ SIGHR

SIGHR: Side Information Guided High-Dimensional Regression
๐Ÿ”— GitHub Repository
๐Ÿ“ Enhances predictive modeling by incorporating auxiliary data in high-dimensional analyses.


๐Ÿ”„ semipadd2pop

semipadd2pop: Semiparametric Additive Modeling
๐Ÿ”— GitHub Repository
๐Ÿ“ Combines multiple datasets for flexible semiparametric additive modeling.


๏ฟฝ Mixed.SVM

Mixed.SVM: Bayesian Mixed Effects SVM
๐Ÿ”— GitHub Repository
๐Ÿ“ Models daily substance use disorder patterns using Bayesian mixed effects support vector machines. โ€”