id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-350240-bmppif8g	Girardi, Paolo	Robust inference for nonlinear regression models from the Tsallis score: application to COVID‐19 contagion in Italy	2020-08-12		.txt	text/plain	3228	181	57	title: Robust inference for nonlinear regression models from the Tsallis score: application to COVID‐19 contagion in Italy In particular, we focus on deaths and intensive care unit hospitalizations data, that are expected to aid the detection of the time when the peaks and the upper asymptotes of contagion, both in daily new cases and total cases, are reached, so that preventive measures (such as mobility restrictions) can be applied and/or relaxed. In contrast, the asymptotic distribution of the scoring rule ratio statisis a linear combination of independent chi-square random variables with coefficients related to the eigenvalues of the matrix J(θ)K(θ) −1 (Dawid et al., 2016) . The robust fits (Tsallis estimates and 95% confidence intervals) of the parameters e (inflection point) and d (upper asymptote) for the models are summarized in Tables 1 and 2 for DD and ICU, respectively.	./cache/cord-350240-bmppif8g.txt	./txt/cord-350240-bmppif8g.txt