An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Differentiated effect of advertising: Joint vs. separate consumption

In a context of intense competition, cooperative advertising between firms is critical. Accordingly, the objective of this article is to analyze the potential differentiated effect of advertising on two basic consumption patterns: individual products (i.e. hotel, restaurant) vs. bundle (i.e. hotel + restaurant). This research adds to the extant literature in that, for the first time, this potential differentiated effect is examined through a hierarchical modelling framework that reflects the way people make their decisions: first, they decide whether to visit or not a region; second, whether to purchase an advertised product in that region; and third, whether to buy products together or separately at the region. The empirical analysis, applied to a sample of 11,288 individuals, shows that the influence of advertising is positive for the decisions to visit and to purchase; however, when it comes to the joint or separate consumption, advertising has a differentiated effect: its impact is much greater on the joint alternative (“hotel + restaurant”) than the separate options (“hotel” and “restaurant”). Also, the variable distance moderates the advertising effect.

Lightweight peer-to-peer secure multi-party VoIP protocol

Multi-party voice-over-IP (MVoIP) services provide economical and convenient group communication mechanisms for many emerging applications such as distance collaboration systems, on-line meetings and Internet gaming. In this paper, we present a light peer-to-peer (P2P) protocol to provide MVoIP services on small platforms like mobile phones and PDAs. Unlike other proposals, our solution is fully distributed and self-organizing without requiring specialized servers or IP multicast support.