in this paper, we obtain  bayesian prediction intervals as well as bayes predictive estimatorsunder square error loss for generalized order statistics when the distribution of the underlying population belongs to a family which includes several important distributions.

Wheeler WC and Pickett KM (2008. Topology-Bayes versus clade-Bayes in phylogenetic analysis. Mol Biol Evol. 25:447-453.) discuss two ways of summarizing the posterior probability distribution of a Bayesian phylogenetic analysis, which they refer to as "topology-Bayes" and "clade-Bayes." They claim that the clade-Bayes approach leads to problems such as "exaggerated clade support, inconsistently...

Introduction: All of the Imaging modalities have advantages and disadvantages alone. So if we want to have the best and perfect image, combining these modalities produces something we desired. PET-MR images consist of morphologic and metabolic data. MRI and PET provide high spatial and contrast resolution and high sensitivity and molecular information respectively. Hybrid PET-...

In many areas of epidemiologic, demographic and geographical research, inference based on hierarchical spatial regression models is popular and important; for example, in disease mapping, environmental and health monitoring studies. Several estimation and inferential procedures have been proposed for these models, utilizing a variety of methods such as estimating equations, empirical Bayes and ...

BACKGROUND AND AIMS It has been proposed that more use should be made of Bayes factors in hypothesis testing in addiction research. Bayes factors are the ratios of the likelihood of a specified hypothesis (e.g. an intervention effect within a given range) to another hypothesis (e.g. no effect). They are particularly important for differentiating lack of strong evidence for an effect and evidenc...

This study investigates regional heart motion abnormality detection via multiview fusion in cine cardiac MR images. In contrast to previous methods which rely only on short-axis image sequences, the proposed approach exploits the information from several other long-axis image sequences, namely, 2-chamber, 3-chamber and 4-chamber MR images. Our analysis follows the standard issued by American He...

Naive Bayes The multinomial Naive Bayes model on a dictionary is a familiar option for text classification, e.g. (Gale, Church, & Yarowski 1992), (McCallum & Nigam 1998). When there are additional features, the Naive Bayes model has also a natural extension: We simply assume that each additional feature is independent of all the others, conditional upon . In this case, we invert Bayes’ Law by o...

This paper mainly deals with various classification algorithms namely, Bayes. NaiveBayes, Bayes. BayesNet, Bayes. NaiveBayesUpdatable, J48, Randomforest, and Multi Layer Perceptron. It analyzes the hepatitis patients from the UC Irvine machine learning repository. The results of the classification model are accuracy and time. Finally, it concludes that the Naive Bayes performance is better than...