Bayesian Effect Fusion for Categorical Predictors

Activity: Talk or presentation › Contributed talk › unknown

Description

We propose sparse Bayesian modelling of the effects of categorical, i.e. nominal and ordinal covariates in regression type models. Sparsity is achieved by specifying spike and slab prior distributions and posterior inference relies on MCMC methods. For illustration we analyse Austrian data from EU-SILC 2010, where we model the effects of social and demographic characteristics on income.
Period22 Sept 2014
Event titleENBIS 14
Event typeConference
LocationAustriaShow on map

Fields of science

  • 509013 Social statistics
  • 102009 Computer simulation
  • 509 Other Social Sciences
  • 101018 Statistics

JKU Focus areas

  • Social and Economic Sciences (in general)

Documents & Links

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