provides the mechanics for learning
from real-world data based on statistical models that can be
simple or very complex. Because Bayesian statistics is
based exclusively on the laws of probability, it is easy to
understand but very powerful; when applied correctly, it leads
to optimal decisions.
Gelman et al.
In Fully Bayesian computing
one programs directly with probability
distributions to build a statistical model
for observed data. Everything else becomes trivial — and
provably optimal. That includes decisions,
forecasts, uncertainty quantification, risk assessments,
control algorithms and measurements of underlying states.
Kerman and Gelman
is a new probabilistic programming
language that combines modern programming languages with
direct support for Bayesian inference and dynamical
writes Baysig code for you
to support data analysis.