13 citations · 19 across the 6 of their papers we have counts for
6 papers
Gaussian Graphical Models for Partially Observed Multivariate Functional Data
Marco Borriero, Luigi Augugliaro, Gianluca Sottile +1
In many applications, the variables that characterize a stochastic system are measured along a second dimension, such as time. This results in multivariate functional data and the…
Functional Gaussian Graphical Regression Models For Air Quality Data
Rita Fici, Gianluca Sottile, Luigi Augugliaro +1
Functional data describe a wide range of processes, such as growth curves and spectral absorption. In this study, we analyze air pollution data from the In-service Aircraft for a G…
The CDF penalty:sparse and quasi unbiased estimation in regression models
Daniele Cuntrera, Luigi Augugliaro, Vito M. R. Muggeo
In high-dimensional regression modelling, the number of candidate covariates to be included in the predictor is quite large, and variable selection is crucial. In this work, we pro…
Sparse inference of the human hematopoietic system from heterogeneous and partially observed genomic data
Gianluca Sottile, Luigi Augugliaro, Veronica Vinciotti +2
Hematopoiesis is the process of blood cell formation, through which progenitor stem cells differentiate into mature forms, such as white and red blood cells or mature platelets. Wh…
The conditional censored graphical lasso estimator
Luigi Augugliaro, Gianluca Sottile, Veronica Vinciotti
In many applied fields, such as genomics, different types of data are collected on the same system, and it is not uncommon that some of these datasets are subject to censoring as a…
L1-Penalized Censored Gaussian Graphical Model
Luigi Augugliaro, Antonino Abbruzzo, Veronica Vinciotti
Graphical lasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection…