statespace 1.3.4

state-space distributions and decisions

uncertainty, confidence, knowledge

their evolution with time and various processes, including noise and observations

risk and the cost of errors

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

Capital Ideas: The Improbable Origins of Modern Wall Street, Peter L. Bernstein

Stochastic Processes and Filtering Theory, Andrew H. Jazwinski

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation, Richard Bookstaber

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

in ubuntu, install or upgrade os-level dependencies

sudo apt-get -qq update -qy
sudo apt-get -qq install -y python3.6 python3-venv python3-pip

clone the git project, start a venv virtual environment, install the package, and test

git clone [e-mail]:noahhsmith/statespace.git statespace
cd statespace
python3 -m venv venv
. venv/bin/activate (same as source venv/bin/activate)
python3 setup.py install
python3 statespace --xbp

usage hints

~/statespace$ venv/bin/python -m statespace -h
usage: statespace [-h] [--lzbp] [--xbp] [--spbp] [--sspf] [--abp]

optional arguments:
  -h, --help  show this help message and exit
  --lzbp      linearized bayesian processor, linearized kalman filter
  --xbp       extended bayesian processor, extended kalman filter
  --spbp      sigma-point bayesian processor, unscented kalman filter
  --sspf      state space particle filter, sequential monte carlo processor
  --abp       adaptive bayesian processors, joint bayesian state/parameteric
              processors