Point process modeling is gaining increasing attention, as point type data are emerging in a large variety of scientific applications. In this article, motivated by neuronal spike trains study, we propose novel regression model, where both the response and predictor can be high-dimensional process. We model effects through conditional intensities using set basis transferring functions convoluti...

Modern data, such as occurring in chemical engineering, typically entail large collections of samples with numerous dimensional components (or attributes). Visualizing the samples in relation of these components can bring valuable insight. For example, one may be able to see how a certain chemical property is expressed in the samples taken. This could reveal if there are clusters and outliers t...

analytic hierarchy process (ahp) has been criticized considerably for possible rank reversal phenomenon caused by the addition or deletion of an alternative. while in many cases this is a perfectly valid phenomenon, there are also many cases where ranks should be preserved. our findings indicate that using the geometric mean reduces the variance in ratings substantially; hence, yielding lower i...