dosearch: R Package for Identifying General Causal Queries
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Updated
Jul 16, 2024 - R
dosearch: R Package for Identifying General Causal Queries
cfid: R package for identifying counterfactuals.
R Package for Simultaneous Multi-Bias Analysis
CausalVerse: An R toolkit expediting causal research & analysis. Streamlines complex methodologies, empowering users to unveil causal relationships with precision. Your go-to for insightful causality exploration.
causalMGM is an R package that allow users to learn undirected and directed (causal) graphs over mixed data types (i.e., continuous and discrete variables).
CAusal Reasoning for Network Identification with integer VALue programming in R
Comparing effectiveness of the most common causal machine learning methods across various treatment effect, model complexities, data dimensions and sample sizes.
Political Data Science Project: Environmental Impact Evaluation of Bicycle Sharing (Grade: 20/20)
causaleffect: R package for identifying causal effects.
Time-concordant event cascades in the pathogenesis of adverse hepatic effects derived using transcriptomics and histopathology data from longitudinal studies in rats.
An R package for learning context-specific causal models, called CStrees, based on observational, or a mix of observational and interventional, data.
This is a project by Asmir Muminovic and Lukas Kolbe, which was created for the Applied Predictive Analytics class held by the Chair of Information Systems at the Humboldt University of Berlin
How to make common social science diagrams using DiagrammeR and Graphviz
Work done for University of Pittsburgh course "Principles of Data Science" (STAT 1261) with Dr. Junshu Bao in Fall semester of 2018.
R Code for graphical causal models including some undirected one. Models include LiNGAM, LOFS, Patel's tau, graphical lasso, and PC algorithm.
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