Bayesian Quanile Matching Estimation
Project description
Bayesian Quantile Matching Estimation using Order Statistics
BQME is a package that allows users to fit a distribution to observed quantile data. The package uses Order Statistics as the noise model, which is more robust than e.g. Gaussian noise model (mean squared error). The paper describing the theory can be found on arxiv: https://arxiv.org/abs/2008.06423. The notebooks for the experiments in the paper are moved to https://github.com/RSNirwan/BQME_experiments.
Install
Clone the repository and install via pip
git clone https://github.com/RSNirwan/bqme
cd bqme
pip install .
Install with dev dependencies
pip install -e .[dev]
if using ZSH, do the following pip install -e ".[dev]"
Usage
To fit a Normal distribution to observed quantile data, we do
from bqme.distributions import Normal, Gamma
from bqme.models import Normal_qm
N, q, X = 100, [0.25, 0.5, 0.75], [-0.1, 0.3, 0.8]
# define prior
mu = Normal(0, 1, name='mu')
sigma = Gamma(0, 1, name='sigma)
# define likelihood
model = Normal_qm(mu, sigma)
# fit model
fit = model.sampling(N, q, X)
Todos
- make package available on PyPI
- use sphinx as documentation tool
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.