Search results for " statistica"
showing 10 items of 2672 documents
Inferring slowly-changing dynamic gene-regulatory networks
2015
Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experi…
Similarity of GPS Trajectories Using Dynamic Time Warping: An Application to Cruise Tourism
2019
The aim of this research is to propose an analysis of the trajectories of cruise passengers at their destination using Dynamic Time Warping algorithm. Data collected by means of GPS devices relating to the behavior of cruise passengers in the port of Palermo have been analyzed in order to show similarities and differences among their spatial trajectories at destination. A cluster analysis has been performed in order to identify segments of cruise passengers, based on the similarity of their trajectories. The results have been compared in terms of several metrics derived from GPS tracking data in order to validate the proposed approach. Our findings are of interest from a methodological pers…
Feigenbaum graphs: a complex network perspective of chaos
2011
The recently formulated theory of horizontal visibility graphs transforms time series into graphs and allows the possibility of studying dynamical systems through the characterization of their associated networks. This method leads to a natural graph-theoretical description of nonlinear systems with qualities in the spirit of symbolic dynamics. We support our claim via the case study of the period-doubling and band-splitting attractor cascades that characterize unimodal maps. We provide a universal analytical description of this classic scenario in terms of the horizontal visibility graphs associated with the dynamics within the attractors, that we call Feigenbaum graphs, independent of map…
Le dinamiche del terziario nei Paesi europei: una riflessione sulla base dei dati ufficiali
2009
La maggiore rilevanza assunta dal settore terziario, in concomitanza ad un costante processo di deindustrializzazione, ci ha indotto ad analizzare il fenomeno la cui evoluzione è fortemente legata ai cambiamenti che negli ultimi decenni hanno caratterizzato la struttura produttiva dei sistemi economici più avanzati. Dopo una breve considerazione delle differenti teorie formulate in anni recenti, il presente lavoro esamina, sia a livello globale che con un maggiore dettaglio, le dinamiche della terziarizzazione nell’ambito dell’EU13 per il decennio 1996-2005. A questo scopo si è fatto ricorso ai dati EUROSTAT, riguardanti il manifatturiero e un sub-insieme del terziario privato, derivandone …
A CLASS OF MULTIVARIATE TRANSFORMED-EXPONENTIAL DISTRIBUTIONS
2013
In finance it is commonly accepted that heavy-tailed distributions are appropriate for modelling financial asset return variables and part of the financial literature has recently focused on them. Much less attention has been dedicated to the construction of joint models of asset returns unable to describe an adequate dependence structure between all these variables. In this paper we propose a procedure for constructing multivariate distributions with given heterogeneous heavy-tailed marginal distributions as a possible (under certain conditions) alternative to the copula approach. The procedure bases on the marginal transformation method and, for given plausible specifications of the margi…
Evaluating the performance of a new picking algorithm based on the variance piecewise constant models
2021
In this paper, a new picking algorithm for the automatic seismogram onset time determination is tested on a dataset of simulated waveforms. We aim at capturing the variations in the performance due to some characteristics of both the seismic event and its detection, which in turn affect some characteristics of the waveforms. We therefore simulate seismic events with different magnitude, and assumed to be detected with different distances from the nearest seismic station. Our tests permit to highlight the scenarios most suitable for our algorithm.
Spatio-temporal log-Gaussian Cox processes on earthquake events
2016
This work presents an application of spatio-temporal log-Gaussian Cox processes for the description of earthquake events. To explain the overall spatial trend, spatial geological information in the study area such as faults and volcanoes are introduced in the model. Moreover, an anisotropic specification of the covariance matrix of the Gaussian process is used to improve the explanation of the phenomenon. We apply and compare different models to explain the seismic events occurred in Alaska over the last decades.
Probabilistic Forecast for Northern New Zealand Seismic Process Based on a Forward Predictive Kernel Estimator
2011
In seismology predictive properties of the estimated intensity function are often pursued. For this purpose, we propose an estimation procedure in time, longitude, latitude and depth domains, based on the subsequent increments of likelihood obtained adding an observation one at a time. On the basis of this estimation approach a forecast of earthquakes of a given area of Northern New Zealand is provided, assuming that future earthquakes activity may be based on the smoothing of past earthquakes.
Multiscale processes to describe the Eastern Sicily Seismic Sequences
2018
In this paper, a version of hybrid of Gibbs point process models is proposed as method to characterise the multiscale interaction structure of several seismic sequences occurred in the Eastern Sicily in the last decade. Seismic sequences were identified by a clustering technique based on space-time distance criterion and hierarchical clustering. We focus our analysis on five small seismic sequences, showing that two of these are described by an inhomogeneous Poisson process (not significant interaction among events) while the other three clusters are described by a hybrid-Geyer process (mutiscale interaction between events). The proposed method, although it still needs extensive testing on …
Local Spatio-Temporal Log-Gaussian Cox Processes for seismic data analysis
2022
We propose a local version of the spatio-temporal log-Gaussian Cox processes (LGCPs) employing the Local Indicators of Spatio-Temporal Association (LISTA) functions into the minimum contrast procedure to obtain space as well as time-varying parameters. We resort to the joint minimum contrast method fitting method to estimate the set of second-order parameters for the class of Spatio-Temporal LGCPs. We employ the proposed methodology to analyse real seismic data occurred Greece between 2004 and 2015.