mcen_workhorse: Estimates the clusters and provides the coefficients for an...
In mcen: Multivariate Cluster Elastic Net

mcen_workhorse

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