This paper extends deterministic models for Boolean regression within a Bayesian framework. For a given binary criterion variable Y and a set of k binary predictor variables X 1 ; : : : ; X k , a Boolean regression model is a con-junctive (or disjunctive) logical combination consisting of a subset S of the X variables, which predicts Y. Formally, Boolean regression models include a speciication...

The domestic and international transmission mechanism of fiscal policy shocks are analysed in the United States Germany. Using a Bayesian VAR approach, we find that both these countries expansion is associated with increases output as well private consumption investment. terms trade, which affect shocks, depreciate response to expansion, thus transferring some increased purchasing power abroad....

Using an asymmetric Laplace distribution, which provides a mechanism for Bayesian inference of quantile regression models, we develop a fully Bayesian approach to fitting single-index models in conditional quantile regression. In this work, we use a Gaussian process prior for the unknown nonparametric link function and a Laplace distribution on the index vector, with the latter motivated by the...

The main goals of this paper are to show the impact of the basic assumptions for the cover channel characteristics as well as the impact of different training/testing set generation strategies on the statistical detectability of exemplary chosen audio hiding approaches known from steganography and watermarking. Here we have selected exemplary five steganography algorithms and four watermarking ...