initializations: Initializations for Various EM Algorithms in 'mixtools'

In mixtools: Tools for Analyzing Finite Mixture Models

Initializations for Various EM Algorithms in 'mixtools'

Description

Internal intialization functions for EM algorithms in the package mixtools.

Usage

flaremix.init(y, x, lambda = NULL, beta = NULL, sigma = NULL,
              alpha = NULL)
gammamix.init(x, lambda = NULL, alpha = NULL, beta = NULL, 
              k = 2)
logisregmix.init(y, x, N, lambda = NULL, beta = NULL, k = 2)
multmix.init(y, lambda = NULL, theta = NULL, k = 2)
mvnormalmix.init(x, lambda = NULL, mu = NULL, sigma = NULL, 
                 k = 2, arbmean = TRUE, arbvar = TRUE)
normalmix.init(x, lambda = NULL, mu = NULL, s = NULL, k = 2, 
               arbmean = TRUE, arbvar = TRUE)
poisregmix.init(y, x, lambda = NULL, beta = NULL, k = 2)


regmix.init(y, x, lambda = NULL, beta = NULL, s = NULL, k = 2, 
            addintercept = TRUE, arbmean = TRUE, arbvar=TRUE)
regmix.lambda.init(y, x, lambda = NULL, beta = NULL, s = NULL,
                   k = 2, addintercept = TRUE, arbmean = TRUE,
                   arbvar = TRUE)
regmix.mixed.init(y, x, w = NULL, sigma = NULL, 
                  arb.sigma = TRUE, alpha = NULL, lambda = NULL, 
                  mu = NULL, R = NULL, arb.R = TRUE, k = 2, 
                  mixed = FALSE, addintercept.fixed = FALSE,
                  addintercept.random = TRUE)
repnormmix.init(x, lambda = NULL, mu = NULL, s = NULL, k = 2, 
                arbmean = TRUE, arbvar = TRUE)
segregmix.init(y, x, lambda = NULL, beta = NULL, s = NULL, k = 2,
               seg.Z, psi, psi.locs = NULL)

Details

These are usually not to be called by the user. Definitions of the arguments appear in the respective EM algorithms.

mixtools documentation built on Dec. 5, 2022, 5:23 p.m.