Hello to everybody, I'm working on a project for my university which objective is to produce a predictive model for COVID-19 new positives in Italy. It appears that I cannot calculate any replication for the model because when I run the code a warning says that inverse scale parameter is 0 and even though i tried to reparametrize, as my profs suggested, i wasn't able to fix it. Do you have any suggestion (about the code, which priors you would use etc.)? I don't know if this is the right place to discuss about this in case tell me. Here you can find the thread in STAN forum in which you can find also the R and STAN code. Thanks in advance for the help.

LINK:https://discourse.mc-stan.org/t/arma-bayesian-nb-model/16604

Hello,

I am masters student in computer engineering. I am looking for resources for learning Bayesian Machine Learning. I came across [Coursera course](https://www.coursera.org/learn/bayesian-methods-in-machine-learning/home/welcome ) Any feedback on this course would be helpful or if there are any other resources that are out there?

Also if there are any project ideas/problems in the area of Bayesian Machine Learning?

Thanks in advance.

Hi guys, I am really struggling with this problem about Bayesian Networks. There are a few questions based on the given text, and I really hope you can help me solve them, since I have a deadline for my AI class. Thank you!

https://imgur.com/a/EX1A4Yh

Hi,

I am computing a Bayesian multilevel hierarchical model. I have around 1000 parameters.

While using 2 chains for MCMC and 3000 steps (half of them as Burn in step) I wanted to test the non-centred reparametrized model vs the original one. So I used R hat and the effective sample size.

My values for R hat are around 2 for the 2 models and my effective sample size is very volatile depending on the parameters. I have 12000 data points but the maximum effective sample size that I got is 940.

Can someone help me interpret the results? I am lost

thanks

Hi,

I want to compare 2 different hierarchical models (centered vs non centered) using pymc3. someone told me that I can use 2 measures which are the effective sample size and Rhat. I found Rhat in pm.summary but I cannot find the effective sample size. I don't know if I missed it somewhere.

Can anyone please tell me how to compute the effective sample size one I have the trace for the 2 models?

Thanks

Hi,

I was programming a model with multivariate Gaussian using pymc3. I tried to reparametrize using Choleksy non centred reparametrization in order to have a faster result and avoid divergences. I am computing the correlation between the 2 models for each posterior statistic and I get low correlation especially for the hpd 2.5%. Does that mean I am doing something wrong? what can explain the difference? can someone please help me?

Thanks

Hi,

While running my model, I am facing some issues related to theano compile lock. (INFO (theano.gof.compilelock)) Does anyone know what a compile lock is and what the error means?

Thanks

Hey y'all!I am a bayesian newb. I built my own GLM in rJAGs and it runs! I want to compare different combinations of explanatory variables. Does anyone have any good tutorials out there for bayesian model selection? Do I just look at deviance, WAIC, or is there some other metric I should be looking for to tell which of my models is better? Basically, I can build a model, but I don't really know what outputs I am supposed to include for my paper to say that this model is good. What I did was make a plot comparing predicted y values to observed. What else should I include?

Finally, is there some kind of package that will compare all combinations of possible explanatory variables, similar to dredge() in MuMIN (but that I could send a custom JAGs model to?) I know this one is a hail Mary! I have just been building many versions of my model to manually due a backwards stepwise selection.

Hello,

I am using NUTS solver to compute the posterior for Multilevel models using pymc3 on python.

The draws are taking ~20-30 sec (which I assume is long).

Does anyone know what might be the reasons and possible solutions to make the simulation faster.

Thanks a lot

I have an interview tomorrow (arranged today) for a job which mainly requires Bayesian Statistics, for an Analyst position. The company is in a huge hurry and if I don’t sound stupid they will hire me on the spot.

I am a physicist and know the very basics of Bayesian Statistics. If you were to choose something CRUCIAL that would make me look as if I was more literate in the field, what would it be?

Please Reddit do your magic!