27 citations · 79 across the 12 of their papers we have counts for
13 papers
Functional limit laws for the intensity measure of point processes and applications
Giacomo Francisci, Anand N. Vidyashankar
Motivated by applications to the study of depth functions for tree-indexed random variables generated by point processes, we describe functional limit theorems for the intensity me…
Branching Processes in Random Environments with Thresholds
Giacomo Francisci, Anand N. Vidyashankar
Motivated by applications to COVID dynamics, we describe a branching process in random environments model whose characteristics change when crossing upper and lower thres…
Analytical and statistical properties of local depth functions motivated by clustering applications
Giacomo Francisci, Claudio Agostinelli, Alicia Nieto-Reyes +1
Local general depth () functions are used for describing the local geometric features and mode(s) in multivariate distributions. In this paper, we undertake a rigorous systema…
Robust estimation in controlled branching processes: Bayesian estimators via disparities
M. González, C. Minuesa, I. del Puerto +1
This paper is concerned with Bayesian inferential methods for data from controlled branching processes that account for model robustness through the use of disparities. Under regul…
Dynamics of an Adaptive Randomly Reinforced Urn
Giacomo Aletti, Andrea Ghiglietti, Anand Vidyashankar
Adaptive randomly reinforced urn (ARRU) is a two-color urn model where the updating process is defined by a sequence of non-negative random vectors …
Central limit Theorem for an Adaptive Randomly Reinforced Urn Model
Andrea Ghiglietti, Anand N. Vidyashankar, William F. Rosenberger
The generalized Pòlya urn (GPU) models and their variants have been investigated in several disciplines. However, typical assumptions made with respect to the GPU do not include ur…