The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for whi...

Markov chain Monte Carlo (MCMC) algorithms are used to estimate features of interest of a distribution. The Monte Carlo error in estimation has an asymptotic normal distribution whose multivariate nature has so far been ignored in the MCMC community. We present a class of multivariate spectral variance estimators for the asymptotic covariance matrix in the Markov chain central limit theorem and...

In modern electronics, specifications for products have constantly been tightened due to performance competition. The processes for product development and manufacturing have been developed to meet the tighter specifications and quality requirements. The development of test methods and measurement devices have not been as fast, and as a consequence, the relative impact of measurement errors has...

Models describing business processes in a company nowadays have the drawback that they are not machine-processable for two reasons: First the terminology is not formalized. Second the dynamic semantics of the process model is not formally defined. Thus, many discussions and human work is necessary in order to create and maintain process models. However, with a semantic annotation of process mod...