Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Gollini, Isabella"'
Autor:
Jain, Mayank, Sengar, Vishal Singh, Gollini, Isabella, Bertolotto, Michela, McArdle, Gavin, Dev, Soumyabrata
Ground-based sky imagers (GSIs) are increasingly becoming popular amongst the remote sensing analysts. This is because such imagers offer fantastic alternatives to satellite measurements for the purpose of earth observations. In this paper, we propos
Externí odkaz:
http://arxiv.org/abs/2209.06051
Ground-based Whole Sky Imagers (WSIs) are increasingly being used for various remote sensing applications. While the fundamental requirements of a WSI are to make it climate-proof with an ability to capture high resolution images, cost also plays a s
Externí odkaz:
http://arxiv.org/abs/2106.03073
Autor:
Gollini, Isabella
This chapter investigates the latent structure of bipartite networks via a model-based clustering approach which is able to capture both latent groups of sending nodes and latent variability of the propensity of sending nodes to create links with rec
Externí odkaz:
http://arxiv.org/abs/1905.02659
Autor:
Caimo, Alberto, Gollini, Isabella
A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network connectivity structure using a hierarchical multilayer exponential random g
Externí odkaz:
http://arxiv.org/abs/1811.07025
Autor:
Gollini, Isabella, Rougier, Jonathan
We consider the task of assessing the righthand tail of an insurer's loss distribution for some specified period, such as a year. We present and analyse six different approaches: four upper bounds, and two approximations. We examine these approaches
Externí odkaz:
http://arxiv.org/abs/1507.01853
Autor:
Caimo, Alberto, Gollini, Isabella
In this chapter we review some of the most recent computational advances in the rapidly expanding field of statistical social network analysis using the R open-source software. In particular we will focus on Bayesian estimation for two important fami
Externí odkaz:
http://arxiv.org/abs/1504.03152
Publikováno v:
In Social Networks October 2020 63:134-149
Autor:
Caimo, Alberto, Gollini, Isabella
Publikováno v:
In Computational Statistics and Data Analysis February 2020 142
Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel, we introduce techniques from a particular branch of spatial statistics,
Externí odkaz:
http://arxiv.org/abs/1306.0413
Latent space models (LSM) for network data were introduced by Hoff et al. (2002) under the basic assumption that each node of the network has an unknown position in a D-dimensional Euclidean latent space: generally the smaller the distance between tw
Externí odkaz:
http://arxiv.org/abs/1301.3759