Strange error while passing string as an argument to the function in bnlearn package
Hello Marco,
By any chance, are using that for prediction?
Yes, I am using it for prediction.
To compute P(A = a | whatever you conditioned on), just sum the corresponding weights over the total weight mass. Since no language trickery is involved, this works reliably.
Thank you! It's exactly what I needed. --- BR, Alexandr
On 11 November 2014 23:33, Marco Scutari <marco.scutari at gmail.com> wrote:
Hi Alexandr, On 11 November 2014 00:10, Alexandr M <rus314 at gmail.com> wrote:
Sorry that I formulated my question not very accurately. I form expressions/(logic conditions for parameters evidence and event) dynamically inside the loop and they are sometimes quite long.
By any chance, are using that for prediction? Because predict(..., method = "bayes-lw") does posterior predictions from any set of variables. As an alternative, you can do cpdist(..., method = "lw") which also generates from the posterior distribution:
str(cpdist(fit, node = "A", evidence = list(B = "b"), method = "lw"))
Classes ?bn.cpdist? and 'data.frame': 10000 obs. of 1 variable:
$ A: Factor w/ 3 levels "a","b","c": 1 2 2 3 1 1 1 2 1 1 ...
- attr(*, "weights")= num 0.114 1 1 0.428 0.114 ...
- attr(*, "method")= chr "lw"
To compute P(A = a | whatever you conditioned on), just sum the
corresponding weights over the total weight mass. Since no language
trickery is involved, this works reliably.
Cheers,
Marco
--
Marco Scutari, Ph.D.
Lecturer in Statistics, Department of Statistics
University of Oxford, United Kingdom
Best regards, Alexander Maslov [[alternative HTML version deleted]]