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Similar to the [tutorial on custom losses in SVI](http://pyro.ai/examples/custom_objectives.html), we should have a tutorial on implementing custom MCMC kernels using the new MCMC API. Something simp…
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Halo! Currently, I am trying to fit the light curve of detached binary with an MCMC sampler. My problem is, that I do not know why the solution does not fit with my data, despite the chain seems conve…
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The [documentation](https://turinglang.org/docs/tutorials/docs-12-using-turing-guide/index.html) gives an example of how the sample macro can be used to either condition a model or sample RVs:
```j…
daeh updated
2 months ago
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I am new to Cobaya and the development of Likelihood in this framework. I have written my likelihood and the param file. The params of my file look like this,
```
params:
H0: 67.0
mnu: 0.06
…
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https://github.com/klipto/Uncertainty/blob/master/Uncertain/MarkovChainMonteCarloSampler.cs
The sampler is the main part of the uncertain code.
First try to implement the sampler.
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**Describe the bug**
A clear and concise description of what the bug is.
There is an error in running the tutorial Fitting Correlation Functions with emcee from the website https://halomod.readthe…
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Hello! I am coming from the "Structure Learning with Adaptive Random
Neighborhood Informed MCMC" paper and I am trying to use your sampler as a benchmark.
- Is it intended to run 0_examples.R as t…
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Having a peek through Chapter 3, I notice that you instantiate your `MCMC` objects in a two-step process:
```
model = Model([var1, var2, var3])
sampler = MCMC(Model)
```
There is really no need to e…
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The new version of PyMC allows to choose which variables you actually want to sample, this allows you to skip all deterministics and just do random variables when running MCMC.
Let's try to see if …
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MCMC and SMC samplers should output some extra info for their output including:
- Weights (for SMC)
- Effective sample size
- Acceptance ratio (for MCMC)
- log-probabiltiy (for MCMC [and possibly …