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Motivated by the analysis of the distribution of university grades, which is usually asymmetric, we discuss two informative priors for the shape parameter of the skew-normal distribution, showing that...
A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented. This representation allows circumvention of ma...
In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath channels is exploited ...
We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is prov...
We introduce an extension of the P\'olya tree approach for constructing distributions on the space of probability measures. By using optional stopping and optional choice of splitting variables, the ...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal method for summarising uncertainty and making estimates and predictions using probability statements...
ModernWeb services, such as those at Google, Yahoo!, and Ama- zon, handle billions of requests per day on clusters of thousands of computers. Because these services operate under strict performance ...
The MAPK/ERK pathway is one of the major signal transduction systems which regulates the cellular growth control of all eukaryotes like the cell proliferation and the apoptosis. Because of its importa...
We introduce a class of shape mixtures of skewed distributions and study some of its main properties. We discuss a Bayesian interpretation and some invariance results of the proposed class. We devel...
We analyze complete sequences of successes (hits, walks, and sacrices) for a group of players from the American and National Leagues, collected over 4 seasons. The goal is to describe how players pe...
In this paper, we introduce a Bayesian extended regression model with two-stage priors when the covariate is positive and measured with error. Connections are made with some results in Arellano-Vall...
While Bayes theorem has a 250-year history, and the method of in- verse probability that owed from it dominated statistical thinking into the twen- tieth century, the adjective Byesian was not part ...
A Bayesian Inference for the Extended Skew-Normal Measurement Error Model。
Bayesian Inference for the Skewness Parameter of the Scalar Skew-Normal Distribution。

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