R package: APML0

  • Augmented and penalized minimization method for regularized linear, logistic, and Cox models with L0 penalty, flexible for L1, L2, and network type regularized regression
  • Most intensive computation codes written in C++
  • Available on CRAN

R package: Covariate-dependent-network

  • Estimate covariate-dependent networks through conditional graphical model, in which both the mean and precision matrix depend on covariates
  • Most intensive computation codes written in C++
  • Available on GitHub

R package: INL

  • Integrative network learning for multi-modality data
  • Most intensive computation codes written in C++
  • Available on GitHub

Matlab toolbox: OWMKL

  • Code for implementing outcome weighted multiple kernel learning (OWMKL)
  • Available on GitHub

R package: FSVM

  • Functional support vector machine for classification and regression problems
  • Available on GitHub

R package: ICATemporalNetwork

  • Temporal causal network learning, adjusting for latent non-Gaussian components and separating the temporal network from the contemporaneous network
  • Available on GitHub