examples/

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Version: v1.0.3 Latest Latest
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Published: Nov 29, 2021 License: MIT

README

Basic examples of infergo

  • hello — probabilistic "hello world" — inferring parameters of a normal distribution.
  • gmm — simple Gaussian mixture model. See infergo case studies for a more elaborated model.
  • adapt — NUTS adaptation on the Gaussian mixture model.
  • schools - the 8 schools problem.
  • ppv — inferring pages-per-visit based on a vector of Beta-Bernoulli processes.
  • mt - probabilistic "hello world" with multiple inference goroutines.

Directories

Path Synopsis
gmm
model
Gaussian mixture
Gaussian mixture
model
Inferring parameters of the Normal distribution from observations
Inferring parameters of the Normal distribution from observations
mt
model
Inferring parameters of the Normal distribution from observations
Inferring parameters of the Normal distribution from observations
ppv
model
Determining the best bandwidth for page-per-visit prediction (http://dtolpin.github.io/posts/session-depth/)
Determining the best bandwidth for page-per-visit prediction (http://dtolpin.github.io/posts/session-depth/)
model
The eight schools example as appears in PyStan documentation (and taken from "Bayesian Data Analysis", Section 5.5 by Gelman et al.i): data { int<lower=0> J; // number of schools vector[J] y; // estimated treatment effects vector<lower=0>[J] sigma; // s.e.
The eight schools example as appears in PyStan documentation (and taken from "Bayesian Data Analysis", Section 5.5 by Gelman et al.i): data { int<lower=0> J; // number of schools vector[J] y; // estimated treatment effects vector<lower=0>[J] sigma; // s.e.

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