A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...

This paper proposes a Bayesian, graph-based approach to identification in vector autoregressive (VAR) models. In our Bayesian graphical VAR (BGVAR) model, the contemporaneous and temporal causal structures of the structural VAR model are represented by two different graphs. We also provide an...

A bipartite graph, in which the nodes (or actors in a social network) are partitioned into two sets, can be studied using recent statistical models for dyadic interactions. These models, which are loglinear for the probabilities of dyadic choices or interactions, allow not only arcs or...

The labeling problem considered for this is called face-labeling of the maximal planar or triangular planar graphs in connection with the notion of the . Several triangular planar and maximal planar graphs such as the wheels, the fans etc. have been considered. The face-labeling of maximal...

This paper is about the way to transform any equation into other equations. Moreover, except from that this method allows the transformation of any equation into any other form, there is and the transformation of Cartesian axes into transformed axes. Then, it is plausible with the transformed...

This paper is interested to show the limitations that the 2-Dimensional and 3-Dimensional graphs are showing when we try to visualize the behavior of large number of variables, equations and functions in the same graphical space. Therefore, we suggest the application of multi-dimensional graphs...

Investigating the correlations between graph metrics in various networks is a prosperous research topic that only starts to evolve. Knowledge about graph metrics interrelations may be beneficial in many other aspects of networks studying, starting from optimizing computations to even detecting...