Simone Panzeri’s Post

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PhD Student @ Politecnico di Milano | Mathematical Engineer | Statistical Learning

I am proud to share that our latest (and my first!) contribution entitled "A nonparametric penalized likelihood approach to density estimation of space-time point patterns" has been published in "Spatial Statistics". 💡 We propose a novel nonparametric method to estimate the unknown spatio-temporal probability density function associated with point patterns spatially observed on complex domains of various kinds. ✏ We establish some important theoretical properties of the considered estimator and develop a flexible and efficient estimation procedure. 📊 We thoroughly validate the proposed method, by means of several simulation studies and applications to real-world data. Authors: Blerta Begu, Simone Panzeri, Eleonora Arnone, Michelle Carey, Laura M. Sangalli Code available at: https://lnkd.in/eX9KsgqQ Paper available at: https://lnkd.in/eqKQ_mzz #nonparametric #densityestimation #spatiotemporal #pointpatterns

A nonparametric penalized likelihood approach to density estimation of space-time point patterns

A nonparametric penalized likelihood approach to density estimation of space-time point patterns

sciencedirect.com

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