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This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...
Model comparison for the purposes of selection, averaging and validation is a problem found throughout statistics and related disciplines. Within the Bayesian paradigm, these problems all require the ...
We study the problem of navigating through a database of similar objects using comparisons. This problem is known to be strongly related to the small-world network design problem.
A new approach to adaptive design of clinical trials is proposed in a general multi- parameter exponential family setting, based on generalized likelihood ratio statistics and optimal sequential tes...
We propose a new, nonparametric method for multivariate regression subject to convexity or concavity constraints on the response function. Convexity constraints are common in economics, statistics, ...
This paper deals with the nonparametric estimation in heteroscedastic regression Yi = f(Xi) + i; i = 1; : : : ; n, with incomplete information, i.e. each real random variable i has a density gi wh...
The Increment Ratio (IR) statistic was first defined and studied in Surgailis {\it et al.} (2008) for estimating the long-memory parameter either of a stationary or an increment stationary Gaussian p...

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