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Gaussian Mixture Model estimation
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leungyin/gmm
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/*
NAME:
gmm.h
PURPOSE:
A class that implements a 1-dimensional Gaussian Mixture Model fit with the EM algorithm
PLATFORM:
Tested in 2013 on a MacPro running OSX 10.8.2, but it should be platform independent as long as GSL is available.
DEPENDENCIES:
Requires GNU GSL, which can be found at <http://www.gnu.org/software/gsl/>.
When compiling, use the flags
-lgsl -lgslcblas
or
$(LIB_PATH)/libgsl.a $(LIB_PATH)/libgslcblas.a
USAGE:
The class object contains all the machinery to do a GMM estimation with the EM algorithm.
Upon instantiation, GMM will require the following:
n : number of Gaussians to use
a : array of initial guesses for the mixture coefficients
mean : array of intial guesses for the means
var : array of initial guesses for the variances
Optional parameters:
maxIter : maximum number of iterations of the EM algorithm, default 250
p : desired precision stopping condition, default 1e-5
v : if true, will output progress of each step of EM algorithm, default true
To run the EM algorithm, call GMM::estimate(double *data, int dataSize)
Example:
GMM gmm(n,a,mean,var);
gmm.estimate(data,dataSize);
Copyright (C) 2013 Zachary A Szpiech ([email protected])
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
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