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[CT081]

Session Date & Time : 3E (Aug.23, 17:40-19:20)
Type : Contributed Talk
Abstract : We introduce a Bayesian nonparametric network model based on the truncated Poisson-Dirichlet process prior. In our model, the sociability parameters of the nodes are sorted in descending order. This enables us to focus on the most popular nodes of the network. We will show the simulation algorithm and posterior inference method for this model. Numerical implementations will also be discussed based on simulated observations and real-world datasets.
Classification : 62G05, 62F15, 60G51
Author(s) :
- Junyi Zhang (The Hong Kong Polytechnic University)
- Angelos Dassios (London School of Economics)

Session Date & Time : 3E (Aug.23, 17:40-19:20)
Type : Contributed Talk
Abstract : We exploits regularized regression to estimate the parameters of a simulation model. On each run of the model, we compute some simulated statistics, and we nonparametrically estimate the function linking the generated statistics and the associated parameters. We obtain estimates of the parameters through the previous estimate using the real-world statistics as explanatory variables. We characterize the asymptotic theory of the estimator and we evaluate the approach through a simulation study and an application.
Classification : 62G08, 62E20, 62E17, 62P25
Author(s) :
- Mario Martinoli (Sant'Anna School of Advanced Studies)
- Raffaello Seri (Università degli Studi dell'Insubria)

Session Date & Time : 3E (Aug.23, 17:40-19:20)
Type : Contributed Talk
Abstract : We introduce a flexible semiparametric kernel method for smoothing distributions on nonnegative supports. This multivariate estimator is guided by a given parametric part, here an uncorrelated exponential distribution estimated by maximum likelihood, and a nonparametric part which is a weight function to be smoothed through multiple gamma kernels. Also, a diagnostic model discusses the choice between the parametric, semiparametric and nonparametric approaches. Finally, practical multivariate semicontinuous datasets illustrate the usefulness of the method.
Classification : 62Gxx, 62Hxx
Author(s) :
- Sobom Matthieu Somé (Université Thomas SANKARA)
- Célestin C. Kokonendji (Université Bourgogne Franche-Comté)

Session Date & Time : 3E (Aug.23, 17:40-19:20)
Type : Contributed Talk
Abstract : We investigate a local incremental stationary scheme for the numerical solution of rate-independent systems. The main novelty of our approach in comparison to existing methods is an adaptive choice of the step size for the update of the curve parameter. It is proven that the piecewise affine approximations generated by the algorithm converge (weakly) to a so-called parametrized balanced viscosity solution. Numerical experiments illustrate the theoretical findings and show a significant increase of the step size during sticking and in viscous jumps.
Classification : 65J08, 65K15, 65M12, 65M50
Author(s) :
- Merlin Andreia (TU Dortmund University)
- Christian Meyer (TU Dortmund University)

Session Date & Time : 3E (Aug.23, 17:40-19:20)
Type : Contributed Talk
Abstract : In the talk, we propose a higher order Haar wavelet method for solving parabolic inverse problem with a control parameter. Haar wavelets are used for the spatial discretization whereas backward Euler scheme is used for the temporal discretization. Stability results and error estimates are derived. The proposed method is tested on few examples and the results are compared with some existing literature. The proposed method is performing better in terms of absolute error and maximum error.
Classification : 65T60, 65C30
Author(s) :
- Gopal Priyadarshi (KIng Abdullah University of Science and Technology)