- New laplace_latent_solve(_tol) for getting the mean and covariance (Cholesky) of the modal normal approximation
- The compiler has fewer dependencies, with a smaller binary size and improved speeds.
MC Stan
@mc-stan.org
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Expressive probabilistic programming language for writing statistical models. Fast Bayesian inference. Interfaces for Python, Julia, R, and the Unix shell. A rich ecosystem of tools for validation and visualization. Home mc-stan.org
![print_stan_file(bioassay_stan_file)
data {
int<lower=0> J;
vector[J] x;
array[J] int<lower=0> N;
array[J] int<lower=0, upper=N> y;
}
parameters {
real a;
real<lower=0> b;
}
model {
{a, b} ~ normal(0, 5);
y ~ binomial_logit(N, a + b * x);
}](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:trcknlehdydcvclaqrrhwlo4/bafkreif6uwmy3y4vqwseekgbnr3p3qcjjdtlag3ftesv6nilelc3wsjn54)
