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#							THE CAUSAL DISCOVERY JAR									#
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The purpose of this jar file is to have a single suite in which to run all mixed data causal discovery algorithms suitable for data with latent variables.
You may also perform bootstrapping, complimentary pairs stability selection, and StARS in order to use stability for model selection
This also gives the option of outputting stabilities for every causal prediction in the graph structure

Usage: java -jar causalDiscovery.jar <params>

See Excel sheet for detailed description of parameters

Examples!

1. Run MGM to find an undirected model specifying your own parameters

java -jar causalDiscovery.jar -d data.txt -mgm -l 0.25 0.2 0.4 -o output.txt

2. Run StEPS to get a stability-based lambda parameter set to run MGM and examine edge stabilities

java -jar causalDiscovery.jar -d data.txt -mgm -steps -stabs stabilities.txt -o output.txt

3. Run MGM-PCS with specified parameters

java -jar causalDiscovery.jar -d data.txt -mgm -l 0.25 0.2 0.4 -a 0.05 -alg PCS

4. Run MGM with CPSS and get edge frequencies

java -jar causalDiscovery.jar -d data.txt -mgm -l 0.25 0.2 0.4 -cpss 0.05 -outputOrients orients.txt -o output.txt

5. Run MGM with bootstrap and get edge frequencies

java -jar causalDiscovery.jar -d data.txt -mgm -l 0.25 0.2 0.5 -bootstrap -numBoots 100 -bootBound 50 -outputOrients orients.txt -o output.txt

6. Run Vanilla CPC and get orientation frequencies from StARS

java -jar causalDiscovery.jar -d data.txt -alg CPC -stars 25 -outputOrients orients.txt -o output.txt

7. Run FCI with bootstrapping to get orientation frequencies

java -jar causalDiscovery.jar -d data.txt -alg FCI -bootstrap -outputOrients orients.txt -o output.txt

8. Run FCI-MAX using your own initial undirected skeleton

java -jar causalDiscovery.jar -d data.txt -alg FCIMAX -initGraph graph.txt -o ouput.txt -a 0.01



Coming soon... 

1. Including your own true data generating graph or another graph for automatic comparisons
2. Bootstrapping or using CPSS on an entire procedure (MGM-PCS or MGM-FCI-MAX)