PReMiuM (version 3.0.24)

summariseVarSelectRho: summariseVarSelectRho

Description

This function summarises the posterior distribution of rho, a parameter for variable selection only.

Usage

summariseVarSelectRho(runInfoObj)

Arguments

runInfoObj

Object of type runInfoObj

Value

• A list with the following elements.
• rho
  A matrix that has as many columns as the number of covariates and as many rows as the number of sweeps. This matrix records the samples from the posterior distribution of rho for each covariate at each sweep.
• rhoMean
  Vector with the column means of the matrix rho above. Each value corresponds to the posterior mean of rho for each covariate.
• rhoMedian
  Vector with the column medians of the matrix rho above. Each value corresponds to the posterior median of rho for each covariate.
• rhoLowerCI
  Vector with the column lower confidence intervals of the matrix rho above. Each value corresponds to the lower confidence interval of the posterior distribution of rho for each covariate.
• rhoUpperCI
  Vector with the column upper confidence intervals of the matrix rho above. Each value corresponds to the upper confidence interval of the posterior distribution of rho for each covariate.

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

inputs <- generateSampleDataFile(clusSummaryVarSelectBernoulliDiscrete())

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

rho<-summariseVarSelectRho(runInfoObj)