(AGENPARL) – VENEZIA lun 22 maggio 2023 Speaker: Ruggero Bellio, Università di Udine

The talk will also be available via Zoom https://unive.zoom.us/j/
Meeting ID: 851 5326 8624
Passcode: SanMarco2

Abstract:
This talk illustrates a scalable approach to mixed effects modeling with a probit link and a crossed random effects error structure. Random effects with a crossed structure arise often in social and business applications, a notable setting being that of electronic commerce, with random effects related to customers and purchased items, respectively. In sparsely sampled crossed data the computation for both frequentist and Bayesian estimation can easily grow superlinearly with respect to the sample size, which severely limits the use of these models for very large settings. The proposed method belongs to the class of composite likelihood estimators, and entails the fit of three misspecified reduced models. The resulting estimator is consistent and has an overall computational cost linear in the number of observations.

This is a joint work with Art Owen and Swarnadip Ghosh, Stanford University, and Cristiano Varin, Ca’ Foscari University of Venice.

Bio Sketch:
Ruggero Bellio is Professor of Statistics at the Department Of Economics and Statistics of the University Of Udine. He received the PhD In Statistics from the University of Padova in 2000. 
His research interests are likelihood methods, mixed models and their applications in various fields, statistical computing and data mining.

Fonte/Source: http://www.unive.it/data/agenda/1/75316