Bayesian Matrix Completion for Hypothesis Testing

  • Adapt Bayesian heteroscedastic nonparametric regression to a multiple hypothesis testing framework.
  • Impose a generalized latent factor model to form a non-exchangeable prior for testing.
  • Develop a matrix completion method for a latent matrix.
  • Tackle sparsity of the ToxCast data using hierarchical framework.
  • Enable prediction for non-tested chemical’s activity.
  • Broaden the definition of activity including heteroscedasticity.
  • To appear in Journal of the Royal Statistical Science: Series C.