Bayesian methods are now widely used for analysing radiocarbon dates. We find that the non-informative priors in use in the literature generate a bias towards wider date ranges which does not in general reflect substantial prior knowledge. We recommend using a prior in which the distribution of the difference between the earliest and latest dates has a uniform distribution. We show how such pri...

JNCC2 implements the Naive Credal Classifier 2 (NCC2), i.e., an extension of naive Bayes to imprecise probabilities, designed to return robust classification even on small and/or incomplete data sets, which is often the case in environmental case studies.

Let (Y1,θ1), . . . ,(Yn,θn) be independent real-valued random vectors with Yi, given θi, is distributed according to a distribution depending only on θi for i= 1, . . . ,n. In this paper, best linear unbiased predictors (BLUPs) of the θi’s are investigated. We show that BLUPs of θi’s do not exist in certain situations. Furthermore, we present a general empirical Bayes technique for deriving BLUPs.

Ways in which physical objects interact are explored, and in particular the concept of freedom is analysed. Intuitively, the fit between two shapes in a given spatial configuration is a statement about how much one shape needs to mutilated in order to be made identical to the other. The freedom of one object with respect to another specifies what motions the First object can go through without ...

Article history: Received 17 May 2015 Received in revised form 19 July 2015 Accepted 22 July 2015 Available online 30 July 2015

Classification is one of the major tasks in knowledge discovery and data mining. Naive Bayes classifier, in spite of its simplicity, has proven surprisingly effective in many practical applications. In real datasets, noise is inevitable, because of the imprecision of measurement or privacy preserving mechanisms. In this paper, we develop a new approach, LinEar-Equation-based noise-aWare bAYes c...