PReMiuM (version 3.0.24)

calcDissimilarityMatrix: Calculates the dissimilarity matrix

Description

Calculates the dissimilarity matrix.

Usage

calcDissimilarityMatrix(runInfoObj, onlyLS=FALSE)

Arguments

runInfoObj

Object of type runInfoObj.

onlyLS

Logical. It is set to FALSE by default. When it is equal to TRUE the dissimilarity matrix is not returned and the only method available to identify the optimal partition using 'calcOptimalClustering' is least squares. This parameter is to be used for data

Value

• Need to write this
• disSimRunInfoObj
  These are details regarding the run and in the same format as runInfoObj.
• disSimMat
  The dissimilarity matrix, in vector format. Note that it is diagonal, so this contains the upper triangle diagonal entries.
• disSimMatPred
  The dissimilarity matrix, again in vector format as above, for the predicted subjects.
• lsOptSweep
  The optimal partition among those explored by the MCMC, as defined by the least squares method. See Dahl (2006).
• onlyLS
  Logical. If it set to TRUE the only method available to identify the optimal partition using 'calcOptimalClustering' is least squares.

Authors

David Hastie, Department of Epidemiology and Biostatistics, Imperial College London, UK

Silvia Liverani, Department of Epidemiology and Biostatistics, Imperial College London and MRC Biostatistics Unit, Cambridge, UK

Maintainer: Silvia Liverani

References

Liverani, S., Hastie, D. I., Azizi, L., Papathomas, M. and Richardson, S. (2013) PReMiuM: An R package for Profile Regression Mixture Models using Dirichlet Processes. Submitted. Available at http://uk.arxiv.org/abs/1303.2836

Examples

generateDataList <- clusSummaryBernoulliDiscrete()
inputs <- generateSampleDataFile(generateDataList)
runInfoObj<-profRegr(yModel=inputs$yModel, xModel=inputs$xModel, 
    nSweeps=10, nBurn=20, data=inputs$inputData, output="output", 
    covNames=inputs$covNames,nClusInit=15)

dissimObj<-calcDissimilarityMatrix(runInfoObj)