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I've noticed that there are four distributions in numpy.random that are not supported by Numba yet, i.e.
``` python
multinomial
multivariate_normal
noncentral_chisquare
noncentral_f
```
Is there an…
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We could add some more distributions, at least:
* t-distribution (`"student"`)
* Weibull (`"weibull"`)
Maybe also more multivariate distributions?
* multivariate t-distribution (`"mvstude…
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The `logp` of several multivariate distributions does not work (or is not tested) for arbitrarily batched dimensions. Some cases I could confirm include:
- [x] MvNormal - #6897
- [x] MvStudentT #…
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Dear developers,
Recently, I am trying to write code for calculating MLE via TFP.
I found that TFP will not track the `loc` parameter of multivariate normal when using `GradientTape`
Here is an e…
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I have started thinking about implementing the Multivariate Normal and Multivariate T into distributions. These distributions are too important not to be included in Distributions.
I have a working …
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It would be nice if multivariate and matrixvariate distributions supported axes. Currently, I'm just using a wrapper type, but if there is enough interest it might be worth working with the AxisArrays…
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I don't know if the problem is in reading the files or writing. The sample file after writing looks something like this:
```
zero 5
139840366077272 10611008 1.0 MultivariateDistribution()
13984036607…
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Hi Jonathan:
Sorry to bother you. I got a problem when I run the following code:
import chaospy as cp
C = [[1, 0.5], [0.5, 1]]
mu = [0, 0.5]
x1 = cp.MvNormal(mu, C)
C1 = [[1, 0.4], [0.6,…
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It would be very nice to extend the current functionality to truncated distributions. I already started a proof of concept in truncate branch. This proof of concept covers all the univariate distribut…
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Currently only univariate distributions are supported. A complete implementation would include seamless support for multivariate distributions. The only type that should be changed is the `KernelDensi…