collaborative spectrum sensing (css) is an effective approach to improve the detection performance in cognitive radio (cr) networks. inherent characteristics of the cr have imposed some additional security threats to the networks. one of the common threats is primary user emulation attack (puea). in puea, some malicious users try to imitate primary signal characteristics and defraud the cr user...

2 Lecture 2: Evaluation of Statistical Procedures I 2 2.1 How to compare δ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Comparing risk function I: Bayes risk . . . . . . . . . . . . . . . . . . . . . . 3 2.3 Bayes theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.4 Bayes risk revisited . . . . . . . . . . . . . . . . . . . . . . . . . ...

In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...

Absrract-Two nonparametric methods to estimate the Bayes risk using classified sample sets are described and compared. The first method uses the nearest neighbor error rate as an estimate to bound the Bayes risk. The second method estimates the Bayes decision regions by applying Parzen probability-density function estimates and counts errors made using these regions. This estimate is shown to b...

In this paper we consider the application of a naïve Bayes model for the evaluation of fraud risk connected with government agencies. This model applies probabilistic classifiers to support a generic risk assessment model, allowing for more efficient and effective use of resources for fraud detection in government transactions, and assisting audit agencies in transitioning from reactive to proa...

The problem of state estimation with stochastic uncertainties in the initial state, model noise, and measurement noise is approached using the restricted risk Bayes approach. It is assumed that the a priori distributions of these quantities are not perfectly known but that some a priori information may be available. While offering robustness, the restricted risk Bayes approach incorporates the ...

In this work, fundamental properties of Bayes decision rule using general loss functions are derived analytically and are verified experimentally for automatic speech recognition. It is shown that, for maximum posterior probabilities larger than 1/2, Bayes decision rule with a metric loss function always decides on the posterior maximizing class independent of the specific choice of (metric) lo...

In this paper we consider the application of a naïve Bayes model for the evaluation of fraud risk connected with government agencies. This model applies probabilistic classifiers to support a generic risk assessment model, allowing for more efficient and effective use of resources for fraud detection in government transactions, and assisting audit agencies in transitioning from reactive to proa...