vmm_fit_em_by_ll {MixtureFitting} | R Documentation |
Estimate von Mises Mixture parameters using Expectation Maximization.
Description
Estimates parameters for univariate von Mises mixture using Expectation Maximization algorithm. In this version stopping criterion is the difference between log-likelihood estimates of subsequent iterations.
Usage
vmm_fit_em_by_ll( x, p, epsilon = .Machine$double.eps,
debug = FALSE, implementation = "C" )
Arguments
x |
data vector |
p |
initialization 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, k1, k2, ..., kn ), where Ai is the proportion of i-th component, mui is the center of i-th component and ki is the concentration of i-th component. |
epsilon |
tolerance threshold for convergence |
debug |
flag to turn the debug prints on/off. |
implementation |
flag to switch between C (default) and R implementations. |
Value
Vector of mixture parameters, whose structure is the same as of input parameter's p.
Author(s)
Andrius Merkys
References
Banerjee et al. Expectation Maximization for Clustering on Hyperspheres (2003), manuscript, accessible on: https://web.archive.org/web/20130120061240/http://www.lans.ece.utexas.edu/~abanerjee/papers/05/banerjee05a.pdf