Man pages for snoweye/pmclust
Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

00_pmclust-packageParallel Model-Based Clustering
01-pmclust_pkmeansParallel Model-Based Clustering and Parallel K-means...
10_d.readmeRead Me First Function
11_d.set.globalSet Global Variables According to the global matrix X.gbd...
12_d.paramA Set of Parameters in Model-Based Clustering.
13_d.controlA Set of Controls in Model-Based Clustering.
20-assign.N.sampleObtain a Set of Random Samples for X.spmd
30-em_initialInitialization for EM-like Algorithms
30-em_likeEM-like Steps for GBD
30-em.oneOne EM Step for GBD One E-step and Log Likelihood Based on Current... One M-Step Based on Current Posterior Probabilities
40-generate.basicGenerate Examples for Testing
40-generate.MixSimGenerate MixSim Examples for Testing
41-get.N.CLASSObtain Total Elements for Every Clusters
50-as.dmat.spmdConvert between X.gbd (X.spmd) and X.dmat
50-indep.logLIndependent Function for Log Likelihood
50-mb.printPrint Results of Model-Based Clustering
50-update.classUpdate CLASS.spmd Based on the Final Iteration
60-printFunctions for Printing or Summarizing Objects According to...
zz-internalAll Internal Functions
snoweye/pmclust documentation built on Feb. 4, 2018, 1:06 a.m.