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Martedi' 17 Febbraio 2015 |
ore 16:00 | Enrico Bibbona Università di Torino |
"Fluid" approximations of Density dependent Markov chains We consider large state space continuous time Markov chains arising in many fields such as chemical kinetics, population models, computer science. For a class of such models, namely, for density dependent families of Markov chains that represent the interaction of large groups of identical objects, Kurtz has proposed two kinds of "fluid" approximations (here fliud means that the approximating process has a continuous state space). One is based on ordinary differential equations and provides a deterministic approximation, while the other uses a diffusion process with which the resulting approximation is stochastic (Langevin equations). The computational cost of the deterministic approximation is significantly lower, but the diffusion approximation retains stochasticity and is able to reproduce relevant random features like variance, bimodality, and tail behavior that cannot be captured by a single deterministic quantity. An important limitation of both such methods is that if the original Markov chain has a bounded state space, they only catch the behaviur of the system up to the first visit to the boundary. In order to overcome this drawback, we propose a jump-diffusion approximation, showing on different examples numerical evidence of the quality of the approximation. |

Venerdi' 20 Febbraio 2015 |
ore 16:00 | Magdalena Malina Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna |
Different notions of False Discovery Rate under the logic regression model |

Giovedi' 19 Marzo 2015 |
ore 16:00 | Giovanni Pistone Collegio Carlo Alberto, Moncalieri Italy |
The gradient flow of probabilities on a finite sample space |

Martedi' 14 Aprile 2015 |
ore 16:00 | Massimiliano Povero AdRes, Health Economics & Outcome Research, Torino, Italy |
Pharmacoeconomics: principles, methods and applications |

Giovedi' 11 Giugno 2015 |
ore 14:30 | Sonja Petrovic Applied Mathematics Department, Illinois Institute of Technology, Chicago, IL, US |
Random graphs and networks: estimation and modeling challenges The ubiquity of network data in the world around us does not imply that the statistical modeling and fitting techniques have been able to catch up with the demand. This talk will discuss some of the basic modeling questions that every statistician knows are fundamental, some of the recent advances toward answering them, and the challenges that remain. The specific focus of the talk will be on goodness of fit testing for random graph models. Recent joint work with Despina Stasi and Elizabeth Gross developed a new testing framework for graphs that is based on combinatorics of hypergraphs and model geometry. I will summarize our work by showing simulation results for the p1 model for directed random graphs, which captures propensity of nodes to send and receive edges as well as reciprocation effects. |

Mercoledi' 9 Settembre 2015 |
ore 14:30 | Claudio Macci Università di Roma Tor Vergata |
Asymptotic Results for Runs and Empirical Cumulative Entropies We prove large and moderate deviations for two sequences of estimators based on the order statistics and, more precisely, on spacings. In the first case we deal with runs, and we have sums of independent Bernoulli distributed random variables. In the second case we deal with empirical cumulative entropies, and we have linear combinations of independent exponentially distributed random variables. Joint work with Rita Giuliano and Barbara Pacchiarotti. |

Mercoledi' 29 Settembre 2015 |
ore 15:00 | Rosanna Verde, Antonio Irpino (Seconda Università di Napoli) |
DDA2015: Distributional Data Analysis (Short Course) |

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