We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
After #123, the unsupported_distribution example doesn't make sense and was removed. There should be a new example to show this off.
unsupported_distribution
The pareto distribution might be a good candidate for this
pareto
import numpy as np from conjugate.distributions import Gamma, Pareto from conjugate.models import pareto_gamma prior = Gamma(1, 1) data = [1, 2, 1, 2, 3] posterior = pareto_gamma(n=len(data), ln_x_total=np.log(data).sum(), prior=prior, x_m=1) posterior_samples = posterior.dist.rvs(size=1000) posterior_predictive_samples = Pareto(x_m=1, alpha=posterior_samples).rvs(size=1000)
The text was updated successfully, but these errors were encountered:
Successfully merging a pull request may close this issue.
After #123, the
unsupported_distribution
example doesn't make sense and was removed.There should be a new example to show this off.
The
pareto
distribution might be a good candidate for thisThe text was updated successfully, but these errors were encountered: