We address the problem of providing inference for parameters selected after viewing the data. A frequentist solution to this problem is False Discovery Rate adjusted inference. We explain the role of selection in controlling the occurrence of false discoveries in Bayesian analysis, and argue that Bayesian inference may also be affected by selection – in particular Bayesian inference based on su...

In the field of structural health monitoring (SHM), acquisition acoustic emissions to localise damage sources has emerged as a popular approach. Despite recent advances, task locating within composite materials and structures that contain non-trivial geometrical features, still poses significant challenge. Within this paper, Bayesian source localisation strategy is robust these complexities pre...

OBJECTIVE: To classify patients by age based upon information extracted from their electro-cardiograms (ECGs). To develop and compare the performance of Bayesian classifiers. METHODS AND MATERIAL: We present a methodology for classifying patients according to statistical features extracted from their ECG signals using a genetically evolved Bayesian network classifier. Continuous signal feature...

In this paper, we presented an optimal iterative decision rule for minimizing total cost in designing a sampling plan for machine replacement problem using the approach of dynamic programming and Bayesian inferences. Cost of replacing the machine and cost of defectives produced by machine has been considered in model. Concept of control threshold policy has been applied for decision making. If ...

Agent-oriented software engineering is a new software engineering paradigm that is ideally suited to the analysis and design of complex systems. The main focus of these methodologies is to engineer a complex system in such a way that the correct emergent behavior results. In a complex adaptive system, however, emergent behavior cannot be predicted during analysis and design as it evolves only a...

Abstract: In this paper, we suggest using a skew Gaussian-log Gaussian model for the analysis of spatial censored data from a Bayesian point of view. This approach furnishes an extension of the skew log Gaussian model to accommodate to both skewness and heavy tails and also censored data. All of the characteristics mentioned are three pervasive features of spatial data. We utilize data augme...

in this research, the decision on belief (dob) approach was employed to analyze and classify the states of uni-variate quality control systems. the concept of dob and its application in decision making problems were introduced, and then a methodology for modeling a statistical quality control problem by dob approach was discussed. for this iterative approach, the belief for a system being out-o...

Image priors based on products have been recognized to offer many advantages because they allow simultaneous enforcement of multiple constraints. However, they are inconvenient for Bayesian inference because it is hard to find their normalization constant in closed form. In this paper, a new Bayesian algorithm is proposed for the image restoration problem that bypasses this difficulty. An image...