Calculates cluster assignment and coefficient estimates for a binomial mcen.
mcen_bin_workhorse(beta, delta = NULL, y, x, family = "mbinomial",
ky = NULL, gamma_y = 1, eps = 1e-05, clusterMethod = "kmeans",
clusterIterations = 100, clusterStartNum = 30, cluster_y = NULL,
max_iter = 10)Initial estimate of coefficients.
Tuning parameter for L1 penalty.
Matrix of responses.
Matrix of predictors.
type of likelihood used two options "mgaussian" or "mbinomial"
Number of clusters used for grouping response variables.
Tuning parameter for the penalty between fitted values for responses in the same group.
Convergence criteria
Which clustering method was used, currently support kmeans or kmeanspp
Number of iterations for cluster convergence
Number of random starting points for clustering
An a priori definition of clusters. If clusters are provided they will remain fixed and are not estimated. Objective function is then convex.
The maximum number of iterations for estimating the coefficients
Brad Price <brad.price@mail.wvu.edu>