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Request for vector return from normal_cdf given vector arguments #2468
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Yes all the lpdf and cdf functions return back a scalar. A real in the stan language is a scalar
It would be nice to have a vlpdf style function that returned a vector but we haven't had time to implement it
Reacted by Sean Pinkney and Hans Van CalsterThis would be nice to have for all the copula stuff as well. As the copulas use the marginal cdfs evaluated at each data point.
Reacted by Hans Van Calster and Yichen JiBut I think there would not really be a performance gain..so these functions can live in Stan language is what I would think.
But I think there would not really be a performance gain..so these functions can live in Stan language is what I would think.
+1 ^
also, the row/col-wise framework proposed by @andrjohns would solve this issue.
This feature would really help when we need access to individual observation-level log likelihoods but still want to take advantage of the vectorization in the
_lpdffunctions. Example: https://arxiv.org/abs/2209.09190It would also help in case of interval censoring. See this comment: paul-buerkner/brms#1657 (comment)
I have a PR that examples how we can do this. The main thing is it's a huge rewrite of our distributions that would be a lot of elbow grease effort. It would be nice to have a Stan hackathon to go through the distributions with people and do this split up over several people. We also need a test suite change so that all these are tested for vector returns
Reacted by Hans Van Calster
I wish to execute the normal CDF on vector inputs to obtain a vector of cumulative probabilities. However, I am getting a dimension mismatch error. The error says the return on the right-hand side is of type “real”. The Stan documentation says that the cdf function accepts “reals” arguments and has “reals” returns. I thought this psuedotype “reals” included vectors yet it appears to be returning a scalar.
Example code:
Example error: