This package is a tool for estimating the parameters in a mixtrue model with 2 components. We extend the basic model so it can not only deal with GMM but also Poisson MM. Indeed, the users are allowed to customize their own distribution by passing the specific E-Step, M-Step, likelyhood function, and Infomation Matrix.
Y is affected by Z and hidden variable \Delta \in \lbrace 0, 1 \rbrace, so there are two "kinds" of Y.
And \Delta is affected by X.
©¦ demo.py ©¦ ©À©¤EM_algo ©¦ ©¦ init.py ©¦ ©¦ ©¦ ©À©¤EM_func ©¦ ©¦ ©¦ GaussianModel.py ©¦ ©¦ ©¦ PoissonModel.py ©¦ ©¦ ©¦ init.py ©¦ ©¦ ©¦ ©¦ ©¦ ©¸©¤__pycache__ ©¦ ©¦ GaussianModel.cpython-36.pyc ©¦ ©¦ PoissonModel.cpython-36.pyc ©¦ ©¦ init.cpython-36.pyc ©¦ ©¦ ©¦ ©¸©¤__pycache__ ©¦ init.cpython-36.pyc ©¦ ©¸©¤__pycache__ EM_algo.cpython-36.pyc EM_func.cpython-36.pyc
I put the basic procedure in EM_algo, and prepare the functions related to Gaussian and Poisson distribution in EM_algo.EM_func.
pass
pass
Copyright 2018 Yifan Chen
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