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What's the right abstraction, and base class methods and members that all variational model classes should share? Further, how do we mix and match them up, so it's not as blocky as "MFGaussian" but ca…
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When I try to use pymc3 with CUDA, I get the following message:
```
Using gpu device 0: GeForce GT 610 (CNMeM is disabled, CuDNN not available)
Traceback (most recent call last):
File "/media/ralfe…
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In trying to implement a Categorical variable, I have defined its log-probability as follows:
```
@tensordist(discrete)
def Categorical(p):
def logp(value):
return bound(
log(…
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I'm looking for some clarification on prior specification with rstanarm, since I’m unsure about my interpretation of the documentation. In the code below, I am trying to recreate a cubic multilevel mo…
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On the `master` branch, just downloaded today, the following script
``` python
import numpy as np
import pymc3
model = pymc3.Model()
with model:
theta = pymc3.Dirichlet("theta", np.ones(3))
```…
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Should include:
- Binomial and multinomial variables.
- Beta and gamme density.
- Bounded density (e.g. non negative).
- Empirical density.
- RR, OR, HR...
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I have a transportation model which is kind of Bayes network with 3 nodes: "Calendar","Previous Traffic" and "Traffic".
"Traffic" depends on both "Calendar" and "PreviousTraffic". So I set Figaro's …
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Hi,
Congrats on your project. I really like how you organized it.
I am a relative beginner to belief and bayesian networks but I found the documentation and the examples to be relatively easy to und…
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markov.prior function in Boom package appears to perform bayesian analysis fo Markov Chains. Could it be investigated and, maybe, ported in markovchain package rewriting the core in Rcpp?
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The interface for dealing with posterior distributions for Bayesian computations should include computing posterior-predictive distributions, that is the distribution of new observations conditioned o…
nfoti updated
9 years ago