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With the advent of high-throughput genomic and proteomic technologies, in conjunction with the difficulty in obtaining even moderately sized samples, small-sample classifier design has become a major issue in the biological and medical communities. With small samples, training-data error estimation becomes mandatory. Yet none of the popular error estimation techniques have been rigorously designed...
This paper develops a class of jump stochastic volatility threshold model of VaR Estimation from a Bayesian viewpoint. Bayesian inferences of the unknown parameters are obtained with respect to a subjective prior distribution via Markov chain Monte Carlo(MCMC) method, MCMC algorithm and the value at risk(VaR) predictive are also developed. Based on simulation, if the jump is not Considered, the value...
With the increasing development of e-commerce application, e-commerce system security is facing the heavy challenge. To solve the purpose of intensifying the behavior trustworthiness and controllability of e-commerce system, we focus on building the trustworthy model between e-commerce system and user behaviors and strengthening the manageability of e-commerce systems. This paper by setting up the...
Advancements in nano-scale Integrated Circuits manufacturing technology has resulted in variability of performance metrics. The performance parameters such as Power and Delay are no longer represented deterministically. As a result, circuit designers and manufacturers need to make use of statistical analysis to estimate performance of Integrated Circuits. In this paper we present a new methodology...
Most of projects' cost exceeds 10% of yearly corporations' turnover, a major factor contributing to this loss is the overrun cost of software testing. A lot of events during software Quality Assurance(QA) cycles, the main execution part of testing process, lead the loss. Therefore, there is a great potential benefit to find a way to predict the loss when the risk events arise or when we know they...
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