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Thankyou!! Ive been trawling through quite a few videos to see how to specify priors and assign specific values to their mean and sd, and this is the first one that actually shows how to do it! 😀

The Python package to import is not called pystan anymore, but just stan. So you pip install pystan, but then import stan. Oh and package stan has no member called StanModel. So you may be better served looking at the up-to-date documentation for pystan.

Concise and extremely helpful! Thanks a lot!

👍

Which compilers do you all suggest? Thanks!

What should be RAM size to install rstan. Do you need more than 4GB RAM to install and use Stan program

what makes the attack and defence parameters differ across teams when they are draw from the same distribution?

lol. Nice!

This is the tool I need... I know it gets poo-poohed by the PhD statis crowd, but frankly those guys aren't practitioners and don't understand how to run a damn warehouse. Thank you for open sourcing this...

PIP3 install pystan does not work anymore

Incredible.

Would someone care to explain where the ' my_model.stan' in the fit line came from? I used everything the same and it does not work for me. The fit code did not work.

Wow great stuff!!

Super useful. Thanks a lot for the effort

dont care about stan I just wanted to see cute lady with cool accent. was not disappointed/

How do you do predictions? I am assuming that you need to specify the model type such as "logit" or whatever - but how do you specify the type of model for predictions in the generated quantities block? This is impossible :/

Forecasting possible probables, maybe so maybe knot? Sorry, nothing beats solid footing and, even that's knot the missing variable oddly! Keep working though, I like {STAN} I'm just pretty useless with numbers other than 2count & knot 4get the count! A PROGRAM IS NO PROPHET #justsaying [OI AI IOff}

Is this using depreciated syntax? Doesn't run and doesn't seem to match what I found looking in the docs

Thank you very much. Very helpful.

Why are priors for mu and sigma not explicitly defined?

<3

Great video but Aston Villa are not that good

I can only assume the 92 to 1 ratio of thumbs up to down is based on her beauty. This did not help at all. I do not even know what to ask. I tried copying what she did. She glossed over compiler. is python itself a compiler?

Hello there, I can‘t install Pystan. It show me a very long error code. Has anyone a idea 💡?

how do i make a bayesian autoregressive vector in stan?

really nice!

really charming beauty 🤤

Is this better than r tho

Thank you very much, very well explained

Muy buena tu explicación, saludos desde Bolivia

Finally! An epic aesthetic that is appropriately befitting of an epic open source project.

Hello Ma'am, Great Video! Could you explain How do we set priors?

can i anylize the behaviour of loona stans with stan?

who is your bias?

can I install vivi through stan?

stan loona, yas mama

Amazing videos. Have you thought of creating a patreon?

Great video! How do you animate the base R graphics?

Way too fast! What about the priors

it's really hard to read the last line of code most of the time cause everytime I pause the subtitles go on top of it

I tried to extend your linear fit to a polynomial fit for my data, and am struggling with vectorized syntax for the likelihood in the model. I initially tried: y ~ normal(c + p1 * x + p2 * x * x, sigma); //likelihood Which failed with "No matches for: vector * vector" So I tried: y ~ normal(c + p1 * x + p2 * pow(x,2), sigma); //likelihood Which failed with no match for pow vector int. I tried casting 2 to a real, or making a real parameter which is = 2 with no success either. I could do a non-vectorized format, which works, but there ought to be a vectorized way to do this, and I suspect I am just missing something in the syntax. Normally google is my friend, but after about 30 minutes of googling "STAN polynomial model example" and finding the wrong things, I thought I would ask here and see if you can help. Thanks!

Came here for Stan, stayed for Maggie

Hello, when I run a model, ask me to install rtools I have installed and it is not working :(

Great video

Super creative remote talk! Congratulations to Cristina Barber!

These videos are an amazing resource for a newcomer to the Bayes/HMC/Stan camp, along with the amazing Stan documentation and case studies. Thank you for those!

Really helpful, easy to follow, and relevant. Thank you!