The BEKK model is a popular multivariate GARCH processes. The paper develops a new general asymmetric BEKK structure, which is based on recent empirical findings by semi-parametric news impact curves. For estimating the new model, a Markov chain Monte Carlo technique is used. Empirical results for triviarte asset returns from firms in the US indicate that the deviance information criterion favo...

The standard PAC model focuses on learning a class of functions from labeled examples, where the two critical resources are the number of examples needed and running time. In many natural learning problems, however, unlabeled data can be obtained much more cheaply than labeled data. This has motivated the notion of semi-supervised learning, in which algorithms attempt to use this cheap unlabele...

Model-based approaches towards the segmentation of vascular and cardiac images are presented. For vessel segmentation, prior shape information is introduced based on the notion that vessels are elongated structures. For cardiac segmentation, shape information derived from a training set of segmented images is incorporated in an automatically constructed point distribution model of the heart.

Preferential attachment is a popular model of growing networks. We consider a generalized model with random node removal, and a combination of preferential and random attachment. Using a high-degree expansion of the master equation, we identify a topological phase transition depending on the rate of node removal and the relative strength of preferential vs. random attachment, where the degree d...

A large part of the decision-making problems actors of the power system are facing on a daily basis requires scenarios for day-ahead electricity market prices. These scenarios are most likely to be generated based on marginal predictive densities for such prices, then enhanced with a temporal dependence structure. A semi-parametric methodology for generating such densities is presented: it incl...

preparation of chitosan (cs) microspheres as a novel drug delivery vehicle for intranasal immunization using high, medium and low cs molecular weight (mw) was investigated in this study. diphtheria toxoid (dt) was used as a model antigen. the emulsion-solidification method was adopted for microencapsulation of dt.  in the first step, following the purification of semi-crude dt by the ion-exchan...

We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation constraints estimated with labeled data. This approach encourages the generative model to discover latent structure that is relevant to a prediction task. We estimate parameters with a coordinate ascent algorithm, one s...

This paper investigates the performance of three types of random coefficients logistic regression models; that is, models using parametric, semi-parametric, and nonparametric specifications of the distribution of the random effects. Whereas earlier studies focussed on models with a single random effect, here we look at models with multidimensional random effects (intercepts and slopes). Moreove...