Bayesian optimization analysis with ML-II ε-contaminated prior
In this paper we derive the predictive density function of a future observation when prior distribution for unknown mean of a normal population is a Type-II maximum likelihood ε-contaminated prior. The derived predictive distribution is applied to the problem of optimization of a regression nature in the decisive prediction framework.
Volume (Year): 35 (2008)
Issue (Month): 2 ()
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