Vivekananda Roy

  1. Improving the Convergence Properties of the Data Augmentation Algorithm with an Application to Bayesian Mixture Modelling.

    Authors: Christian P. Robert, James P. Hobert, Vivekananda Roy
    Subjects: Methodology
    Abstract

    Every reversible Markov chain defines an operator whose spectrum encodes the
    convergence properties of the chain. When the state space is finite, the
    spectrum is just the set of eigenvalues of the corresponding Markov transition
    matrix. However, when the state space is infinite, the spectrum may be
    uncountable, and is nearly always impossible to calculate. In most applications
    of the data augmentation (DA) algorithm, the state space of the DA Markov chain
    is infinite.

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