Vivekananda Roy

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We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analyze data on financial returns, which are notoriously heavy-tailed. Let π denote the intractable posterior density that results when this regression model is combined with the(More)
Let f be an integrable function on an infinite measure space (S, S, π). We show that if a regenerative sequence {Xn} n≥0 with canonical measure π could be generated then a consistent estimator of λ ≡ S f dπ can be produced. We further show that under appropriate second moment conditions, a confidence interval for λ can also be derived. This is illustrated(More)
It is known that the robit regression model for binary data is a robust alternative to the more popular probit and logistic models. The robit model is obtained by replacing the normal distribution in the probit regression model with the Student's t distribution. Unlike the probit and logistic models, the robit link has an extra degrees of freedom (df)(More)
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