You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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?
The text was updated successfully, but these errors were encountered:
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?
The text was updated successfully, but these errors were encountered: