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state-space distributions and decisions

Project description

pipeline pypi blog references

uncertainty and confidence, distributions, their evolution with time, noise, and observations, tracking and detection, decisions, risk and the cost of errors, model-based systems, sample-and-propagate, sequential monte-carlo, markov-chain monte-carlo

The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, Sam L. Savage

Bayesian Signal Processing: Classical, Modern, and Particle Filtering Methods, James V. Candy

Time Series Analysis by State Space Methods, James Durbin

Kalman Filtering: Theory and Practice, Mohinder S. Grewal, Angus P. Andrews

Forecasting, Structural Time Series Models and the Kalman Filter, Andrew C. Harvey

current focus is build-test-deploy to kubernetes-engine using cloud-source and cloud-build along the way. build-test-deploy to pypi is mostly a placeholder, ubuntu clone-install-develop of gitlab repo is assumed for now.

sudo apt-get -qq update -qy
sudo apt-get -qq install -y python3.6 python3-venv python3-pip
git clone git@gitlab.com:noahhsmith/statespace.git statespace
cd statespace
python3 -m venv venv
. venv/bin/activate
python3 setup.py develop
pytest
python3 statespace --demo

noah smith - statespace.dev

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