GMM_Wd

Compute 2-Wasserstein distance between two Gaussian mixture models
See: Delon J, Desolneux A. (2019) A Wasserstein-type distance in the space of Gaussian Mixture Models. hal-02178204v2

Read, register and compare point sets from single molecule localization microscopy.

Jean-Karim Heriche

LOMAR

Localization Microscopy Data Analysis

GMM_Wd function

<dl><dt>m1</dt>
<dd>matrix of means of first GMM</dd>
<dt>m2</dt>
<dd>matrix of means of second GMM</dd>
<dt>S1</dt>
<dd>array of covariance matrices of first GMM such that m1[i,] has covariance matrix S1[,,i]</dd>
<dt>S2</dt>
<dd>array of covariance matrices of second GMM such that m2[i,] has covariance matrix S2[,,i]</dd>
<dt>w1</dt>
<dd>(optional) vector of mixture weights of first GMM.</dd>
<dt>w2</dt>
<dd>(optional) vector of mixture weights of second GMM.</dd>
<dt>S</dt>
<dd>(optional) array of pre-computed sqrtm(sqrtm(S1[,,i]) %*% S2[,,j] %*% sqrtm(S1[,,i]))</dd></dl>

Arguments

GMM_Wd — GMM_Wd

<dl>

<dt>m1</dt>
<dd>matrix of means of first GMM</dd>


<dt>m2</dt>
<dd>matrix of means of second GMM</dd>


<dt>S1</dt>
<dd>array of covariance matrices of first GMM such that m1[i,] has covariance matrix S1[,,i]</dd>


<dt>S2</dt>
<dd>array of covariance matrices of second GMM such that m2[i,] has covariance matrix S2[,,i]</dd>


<dt>w1</dt>
<dd>(optional) vector of mixture weights of first GMM.</dd>


<dt>w2</dt>
<dd>(optional) vector of mixture weights of second GMM.</dd>


<dt>S</dt>
<dd>(optional) array of pre-computed sqrtm(sqrtm(S1[,,i]) %*% S2[,,j] %*% sqrtm(S1[,,i]))</dd>

</dl>

GMM_Wd: GMM_Wd

Description

Usage

Value

Arguments