Hi,
We are currently trying to simulate data for 4 variables. Our issue is that we have 2 variables following Poisson distributions, and we can't find any information about simcausal supporting this distribution.
In our case we have the following DAG with 2 colliders, where we investigate whether source code refactoring influence test code refactoring.
SR = Source code refactoring (Bernoulli)
TR= Test code refactoring (Bernoulli)
R_Loc = Lines of code in child commit (Poisson)
R_L = # of locations in child commit (Poisson)
Do you have any suggestion regarding how we could achieve the effect of two Bernoulli variables influencing a variable following a Poisson distribution?
Hi,
We are currently trying to simulate data for 4 variables. Our issue is that we have 2 variables following Poisson distributions, and we can't find any information about simcausal supporting this distribution.
In our case we have the following DAG with 2 colliders, where we investigate whether source code refactoring influence test code refactoring.
SR = Source code refactoring (Bernoulli)
TR= Test code refactoring (Bernoulli)
R_Loc = Lines of code in child commit (Poisson)
R_L = # of locations in child commit (Poisson)
Do you have any suggestion regarding how we could achieve the effect of two Bernoulli variables influencing a variable following a Poisson distribution?