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It would be very helpful to have a function would return a list of distributional objects that make up a mixture distribution so that conjugacy can be used to calculate posteriors where possible. In P…
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## 🚀 Feature
Add PlackettLuce and RelaxedPlackettLuce distributions. It is a simple distribution over permutations.
## Motivation
For optimization over categorical/binary variables (i.e. variat…
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Outlining some notes from an in-person conversation with Andreas:
- When doing `viz.heatMap`, we need to know how many samples there were -- it would be nice if this information was available in margi…
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Dear Brian,
I have a really basic question about how MixSIAR deals with variation in the sources, and have not been able to find the answer in the documentation. I’ve been advising a whole lab of s…
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A posterior predictive check (PPC) for the Cox model would be nice, but it would probably have to be conducted differently than in all other models since the spline estimate of the baseline hazard mak…
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Hi @gfinak, hi @mikejiang,
I was wondering whether there was a way to get the quantiles of each point, for each cluster from a flowClust object., i.e. the quantile of each point with regard to the …
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## Current state of code
As per #239 we have a neat forecast function for models which have had inference on some time span $(1, T)$. The posterior chain can be used to condition the sampling of th…
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## Issue description
Provide a short description.
I wonder if we could implement a custom model instead of GP class model.
Specifically, suppose we build a random forest model, and it also hav…
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I should implement MultiNest (specifically [PyMultiNest](https://github.com/JohannesBuchner/PyMultiNest)) as nested sampling typically converges more quickly than MCMC and can handle multi-modal poste…
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One might want to use `MH`, `HMC`, etc. to sample from a distribution with unknown/intractable normalization factor rather than to sample from a posterior. In theory there's nothing prohibiting this k…