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Criteria
Outcome
Objective
Estimand
Validity
Data compatibility
Data type
Required TS length
Handles few samples
Handles huge datasets
Handles missing data
RS-data proven
Assumptions
Functional form
No unobserved confounders
No interference
Well-defined treatment
Common support
Causal Markov condition
Faithfulness
IDD
Model-specific
Model properties
Explicit process required
Exposure type
Number of variables
Handles lag effects
Propagates uncertainty
Parametric nature
Packages
Language
Usage
Methods
Counterfactual & future simulations
Method name
Experiments
Method name
Ecology-guided Modelling
Method name
Adjusted methods
Method name
Quasi-experiments
Method name
Synthetic controls
Causal ML
Method name
Causal discovery
Method name
Alternative paradigms
Method name
Independent detection
Method name
Versatile tools
Method name
Good practices
A primer on causal graphs
Causal paradigms
Page example
Gallery
Gallery example
DAM on GitHub
Criteria
Model properties
Model properties
This category defines the properties that the suggested models should verify.
Its evaluation varies according to system knowledge, data aspects, and desired model capacities.
Table of contents
Explicit process required
Exposure type
Number of variables
Handles lag effects
Propagates uncertainty
Parametric nature