1 citations · 1 across the 2 of their papers we have counts for
3 papers
stat.ME2025
Sampled Grid Pairwise Likelihood (SG-PL): An Efficient Approach for Spatial Regression on Large Data
Giuseppe Arbia, Vincenzo Nardelli, Niccolo Salvini
Estimating spatial regression models on large, irregularly structured datasets poses significant computational hurdles. While Pairwise Likelihood (PL) methods offer a pathway to si…
econ.EM2024
New accessibility measures based on unconventional big data sources
G. Arbia, V. Nardelli, N. Salvini +1
In health econometric studies we are often interested in quantifying aspects related to the accessibility to medical infrastructures. The increasing availability of data automatica…
stat.ME2024★ 1 cited
Feasible pairwise pseudo-likelihood inference on spatial regressions in irregular lattice grids: the KD-T PL algorithm
Giuseppe Arbia, Niccolo Salvini
Spatial regression models are central to the field of spatial statistics. Nevertheless, their estimation in case of large and irregular gridded spatial datasets presents considerab…