I am looking at the WetGrassSprinklerRain code and I'm trying to adapt it to my own problem where there are even more variables. My problem is a bit simpler, though there are many more variables. I have a file defining a list of ~150 DNA mutations (one per
line) that are associated with some disease. The model I'm imagining is just ~150 nodes, each representing one mutation, all pointing to a single node representing the disease. However, I do not really want to hard code defining the priors and parameters as
in the constructor of the WetGrassSprinklerRain example. Rather, I'd like to just keep them in a collection object like a Dictionary and then iterate through that collection to define those priors and parameters. I think I am able to do that without much issue,
but then I get to the disease node (analogous to WetGrass) and I don't know what to do because it seems that it is defined as a 2D jagged array in the example and in my case it would be a ~151D jagged array. Is there any way to code what I am describing and
construct a discrete bayesian network with n variables dynamically at runtime? Sorry if my question is confusing as I am new to Bayesian Networks and Infer.Net

Thanks,

-Paul