Description Usage Arguments Value
fmlcdEM
Utilizes the EM approach to obtain a mixture
of log-concave densities. Utilizes Gaussian hierarchical clustering to
initilize the posterior probabilities of class affiliation (as proposed
by the package LogConcDEAD by Cule et al.).
1 | fmlcdEM(X, K = 2, posterior, verbose = 0, maxIter = 50)
|
X |
Matrix of data points (one sample per row) |
K |
Number of latent variables (default: 2) |
posterior |
Matrix with posterior probabilities for class affiliation; Initialized if not provided using a Gaussian hierarchical clustering. |
verbose |
Int determining the verboseness of the code; 0 = no output to 3. (default: 0) |
maxIter |
Maximal number of EM iterations. (default: 50) |
Parametrization of the mixture density
params |
List of length K, where each entry contains the hyperplane for one density |
densEst |
Matrix where each row contains the marginal distribution p(x) |
tau |
Marginal distribution over the latent variable p(z) |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.