Open anmwinter opened 7 years ago
The case studies eventually go on the web site repo. Your Stan model has lots of problems you can see in just this fragment:
parameters { //The primary parameters of interest that are to be estimated.
real mu1; // mean of y1
...
real<lower=0> sigma1; // standard deviation of y1
...
}
model { // Where your priors and likelihood are specified. Uniform, cauchy, and normal
// priors might be a good place to start?
mu1 ~ uniform(0, 30); // uniform prior, maybe try half-normal, exp, or half-cauchy
...
y1 ~ normal(mu1, sigma1);
...
The code itself has some problems:
mu1
, then you need to constrain the parameter to have matching lower and upper bounds---Stan models should have a finite log likelihood for all parameter values meeting the declared constraintsThe doc also has some issues
mu1
isn't the mean of y1
, it's a location parameter@bob-carpenter Thanks for the feedback! I'll work on correcting this. This is a learning process for me.
For the moment, we're trying to keep the case studies to best practices recommendations for Stan. We're working on establishing a place for more community oriented sharing of work we wouldn't need to vet so closely. There are prior recommendations on the stan-dev/stan wiki and in the manual regression chapter.
You also don't need blocks with nothing in them and you can vectorize everything. This model should look like this:
data {
int N[2];
vector[N[1]] y1;
vector[N[2]] y2;
}
parameters {
vector[2] mu;
vector<lower=0>[2] sigma;
}
model {
mu ~ normal(0, 10);
sigma ~ cauchy(0, 5);
y1 ~ normal(mu[1], sigma[1]);
y2 ~ normal(mu[2], sigma[2]);
}
It'd be even easier if we had ragged arrays.
Thanks again @bob-carpenter ! I am working on how to vectorize data. I appreciate the model re-write.
ara
Hello,
I asked over on the Pystan group about submitting juypter notebook example models using Pystan. I was directed to over here. I am in the process of moving our models into Pystan so this is a learning process for me.
I created a jupyter notebook here: https://github.com/bioinfonm/bioinfonm.github.io/blob/master/_posts/pystan_musings_part1_img/pystan_three_centirues_english_grain_data.ipynb
The notebook, raw data, and images are all: https://github.com/bioinfonm/bioinfonm.github.io/tree/master/_posts/pystan_musings_part1_img
I was wondering what was the best way to get this vetted and then hosted here as an example for PyStan.
Thank you for the time and consideration, Ara