Alternatives and similar repositories for dbnR

Users that are interested in dbnR are comparing it to the libraries listed below

• robson-fernandes / dbnlearn
  dbnlearn: An R package for Dynamic Bayesian Network Structure Learning, Parameter Learning and Forecasting
  ☆19Updated 5 years ago
• disco-coders / causalDisco
  Tools for causal discovery in R
  ☆21Updated 3 weeks ago
• ModelOriented / treeshap
  Compute SHAP values for your tree-based models using the TreeSHAP algorithm
  ☆93Updated last week
• cran / bnlearn
   This is a read-only mirror of the CRAN R package repository. bnlearn — Bayesian Network Structure Learning, Parameter Learning and Infe…
  ☆62Updated 5 months ago
• ykang / gratis
  GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
  ☆77Updated 2 weeks ago
• maxto / Time-Series-Clustering
  Time-Series Clustering: Overview, R-packages
  ☆46Updated 8 months ago
• cran / pcalg
   This is a read-only mirror of the CRAN R package repository. pcalg — Methods for Graphical Models and Causal Inference. Homepage: https…
  ☆35Updated last year
• NorskRegnesentral / shapr
  Explaining the output of machine learning models with more accurately estimated Shapley values
  ☆175Updated last week
• liuyanguu / SHAPforxgboost
  SHAP (SHapley Additive exPlnation) visualization for 'XGBoost' in 'R'
  ☆129Updated last month
• bd2kccd / r-causal
  R Wrapper for Tetrad Library
  ☆35Updated last year
• lnferreira / ts2net
  An R package to transform time series into networks
  ☆20Updated last year
• tlverse / tlverse-handbook
  🎯 Targeted Learning in R: A Causal Data Science Handbook
  ☆60Updated last year
• lorismichel / drf
  Distributional Random Forests (Cevid et al., 2020)
  ☆45Updated 3 weeks ago
• AnaRitaNogueira / Methods-and-Tools-for-Causal-Discovery-and-Causal-Inference
  This repository is used as a support for the paper "" (to be named)
  ☆27Updated 4 years ago
• migariane / TutorialCausalInferenceEstimators
  Introduction to the mosts common estimators and computation in causal inference for epidemiologists: A tutorial
  ☆39Updated 5 years ago
• jantonelli111 / HDconfounding
  R package to implement high-dimensional confounding adjustment using continuous spike and slab priors
  ☆10Updated 6 years ago
• vdorie / aciccomp
  Code to run submissions for the Atlantic Causal Inference Competition
  ☆45Updated last year
• nredell / shapFlex
  An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
  ☆74Updated 5 years ago
• bgreenwell / fastshap
  Fast approximate Shapley values in R
  ☆128Updated 8 months ago
• vdorie / bartCause
  Causal Inference using Bayesian Additive Regression Trees
  ☆85Updated 6 months ago
• drizopoulos / JMbayes
  Joint Models for Longitudinal and Survival Data using MCMC
  ☆59Updated 5 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• theodds / SoftBART
  ☆33Updated 4 months ago
• CausalInference / pygformula
  The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…
  ☆31Updated 2 months ago
• jaredsmurray / bcf
  Bayesian Causal Forests
  ☆53Updated last year
• hanase / BMA
  R package for Bayesian model averaging
  ☆40Updated last year
• sachsmc / causaloptim
  An Interface to Specify Causal Graphs and Compute Balke Bounds
  ☆22Updated 11 months ago
• santikka / causaleffect
  causaleffect: R package for identifying causal effects.
  ☆37Updated 4 months ago
• ModelOriented / kernelshap
  Different SHAP algorithms
  ☆57Updated 4 months ago
• stablemarkets / BayesianTutorials
  Implementing MCMC sampling from scratch in R for various Bayesian models
  ☆111Updated 2 years ago