Variational Bayes algorithm for normal inverse Gaussian mixture models
Project description
Variational Bayes algorithm for Normal Inverse Gaussian Mixture Models
Installation
The package can be build using poetry and installed using pip:
pip install vbnigmm
Examples
If you want to apply vbnigmm to your data, you can run the following code:
from vbnigmm import NormalInverseGaussMixture as Model
# x is numpy.ndarray of 2D
model = Model()
model.fit(x)
label = model.predict(x)
Citation
If you use vbnigmm in a scientific paper, please consider citing the following paper:
Takashi Takekawa, Clustering of non-Gaussian data by variational Bayes for normal inverse Gaussian mixture models. arXiv preprint arXiv:2009.06002 (2020).
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