Closed nightscape closed 8 years ago
Hi Martin,
sorry for the delay, I'm currently traveling so I haven't had time to properly review this PR earlier.
Unfortunately, the way you implemented the two continuous distributions won't work as expected for most inference methods. The reason is that the methods you added sample the distribution as they create random variables, rather than during the inference. E.g. a call to normal
will generate a constant random variable taking the value returned by randomGenerator.nextGaussian
with probability one, rather than a random variable with a normal distribution. This happens to work if you use simple rejection sampling to infer the distribution, but it will not give the expected result if you use e.g. exact inference.
Implementing proper support for continuously distributed variables in Odds will take some work (the current implementation contains support only for discrete distributions) and I haven't had the time to do it so far. Feel free to add an GitHub issue about that.
Too old ;)
I added continuous uniform and normal distributions to RandOps. Is this the correct way to do it? If so I would add some more continuous distributions.
Best Martin