This paper analyzes the post decryption error probability in Counter mode operation in an error prone communications channel. A finite state stochastic model has been developed that quantifies the impact of bit errors in the ciphertext and cipher synchronization counter. Analytical results are used to compute post decryption error probabilities and are found to be in reasonable agreement with t...

We introduce a new technique to model check reachability properties on Interval Discrete-Time Markov Chains (IDTMC). We compute a sound overapproximation of the probabilities of satisfying a given property where the accuracy is characterized in terms of error bounds. We leverage affine arithmetic to propagate the first-order error terms. Higher-order error terms are bounded using interval arith...

The problem of setting a confidence interval with fixed proportional accuracy for the mean of a normal distribution is considered. A sequential procedure is proposed; and asymptotic expansions for its average coverage probabilities and its expected sample size are obtained. The procedure is shown to have asymptotically minimal expected sample size, subject to a constraint on the error probabili...

The use of posterior probabilities to summarize genotype uncertainty is pervasive across genotype, sequencing and imputation platforms. Prior work in many contexts has shown the utility of incorporating genotype uncertainty (posterior probabilities) in downstream statistical tests. Typical approaches to incorporating genotype uncertainty when testing Hardy-Weinberg equilibrium tend to lack cali...

We derive a large deviation result for the log-likelihood ratio for testing simple hypotheses in locally stationaryGaussian processes. This result allows us to find explicitly the rates of exponential decay of the error probabilities of type I and type II for Neyman–Pearson tests. Furthermore, we obtain the analogue of classical results on asymptotic efficiency of tests such as Stein’s lemma an...

Tsallis’ ‘statistical thermodynamic’ formulation of the nonadditive entropy of degree-α is neither correct nor self-consistent. It is well known that the maximum entropy formalism [1], the minimum discrimination information [2], and Gauss’ principle [3, 4] all lead to the same results when a certain condition on the prior probability distribution is imposed [5]. All these methods lead to the sa...

Within the context face expression classification using the facial action coding system (FACS), we address the problem of detecting facial action units (AUs). The method adopted is to train a single error-correcting output code (ECOC) multiclass classifier to estimate the probabilities that each one of several commonly occurring AU groups is present in the probe image. Platt scaling is used to ...