R: Multivariate Cluster Elastic Net

# Multivariate Cluster Elastic Net

## Documentation for package ‘mcen’ version 1.2.1

- DESCRIPTION file

## Help Pages

beta_adjust | Adjusts the value of the coefficients to account for the scaling of x and y.
beta_adjust_bin | Adjusts the value of the binomial coefficients to account for the scaling of x.
bin_horse | The workhorse function for the binomial updates in mcen. It uses IRWLS glmnet updates to solve the regression problem.
CalcHorseBin | Creates the the working response for all responses for glmnet binomial family
CalcHorseEBin | Creates the probabilities and working response for the glmnet update for a given response with a binomial family
cluster | Wrapper function for different clustering methods
cluster.vals | Returns the cluster values from a cv.mcen object.
coef.cv.mcen | Returns the coefficients from the cv.mcen object with the smallest cross-validation error.
coef.mcen | Returns the coefficients from an mcen object.
cv.mcen | Cross validation for mcen function
get_best_cvm | Gets the index position for the model with the smallest cross-validation error.
matrix_multiply | matrix multiply
mcen | Fits an MCEN model
mcen.init | Provides initial estimates for the mcen functionF
mcen_bin_workhorse | Calculates cluster assignment and coefficient estimates for a binomial mcen.
mcen_workhorse | Estimates the clusters and provides the coefficients for an mcen object
predict.cv.mcen | Makes predictions from the model with the smallest cross-validation error.
predict.mcen | predictions from a mcen model
pred_eval | Calculates the out of sample likelihood for an mcen object
pred_eval.mbinom_mcen | Evaluates prediction error for multiple binomial responses.
pred_eval.mgauss_mcen | Calculates the prediction error for a mgauss_mcen object.
print.cv.mcen | Prints nice output for a cv.mcen object.
print.mcen | Prints nice output for an mcen object.
randomly_assign | randomly assign n samples to k groups
SetEq | SetEq test set equivalence of two clustering sets
squared_error | Calculates sum of squared error between two vectors or matrices
vl_binom | Calculates out of sample error on the binomial likelihood