cmm_init_vector_kmeans {MixtureFitting} | R Documentation |
Estimate Cauchy Mixture parameters using Expectation Maximization.
Description
Estimate an initialization vector for Cauchy mixture fitting using k-means. R implementation of k-means in kmeans() is used to find data point assignment to clusters. Then several iterations of Cauchy mixture fitting (per Nahy 2006) is used to derive mixture parameters.
Usage
cmm_init_vector_kmeans( x, m, iter.cauchy = 20 )
Arguments
x |
data vector |
m |
number of mixture components |
iter.cauchy |
number of iterations to fit a single Cauchy component. |
Value
Parameter vector of 3*n parameters, where n is number of mixture components. Structure of p vector is p = c( A1, A2, ..., An, mu1, mu2, ..., mun, gamma1, gamma2, ..., gamman ), where Ai is the proportion of i-th component, mui is the center of i-th component and gammai is the Cauchy scale of i-th component.
Author(s)
Andrius Merkys
References
Ferenc Nahy. Parameter Estimation of the Cauchy Distribution in Information Theory Approach (2006). Journal of Universal Computer Science