| mcen_workhorse {mcen} | R Documentation |
Estimates the clusters and provides the coefficients for an mcen object
Description
Estimates the clusters and provides the coefficients for an mcen object
Usage
mcen_workhorse(beta, delta = NULL, xx, xy, family = "mgaussian",
ky = NULL, gamma_y = 0.5, eps = 1e-05, clusterMethod = "kmeans",
clusterIterations = 100, clusterStartNum = 30, cluster_y = NULL,
max_iter = 10, x = x)
Arguments
beta |
The initial value of the coefficients |
delta |
The sparsity (L1) tuning parameter |
xx |
Matrix of transpose of x times x. |
xy |
Matrix of transpose of x times y. |
family |
Type of likelihood used two options "mgaussian" or "mbinomial" |
ky |
Number of clusters for the response |
gamma_y |
Penalty for the y clusters difference in predicted values |
eps |
Convergence criteria |
clusterMethod |
Which clustering method was used, currently support kmeans or kmeanspp |
clusterIterations |
Number of iterations for cluster convergence |
clusterStartNum |
Number of random starting points for clustering |
cluster_y |
An a priori definition of clusters. If clusters are provided they will remain fixed and are not estimated. Objective function is then convex. |
max_iter |
The maximum number of iterations for estimating the coefficients |
x |
The design matrix |
Author(s)
Ben Sherwood <ben.sherwood@ku.edu>, Brad Price <brad.price@mail.wvu.edu>