...da leggere insieme a questo On single point forecasts for fat-tailed variables by Nassim Nicholas Taleb, Yaneer Bar-Yam, and Pasquale Cirillo ABSTRACT We discuss common errors and fallacies when using naive “evidence based” empiricism and point forecasts for fat-tailed variables, as well as the insufficiency of using naive first-order scientific methods for tail risk management. We use the COVID-19 pandemic as the background for the discussion and as an example of a phenomenon characterized by a multiplicative nature, and what mitigating policies must result from the statistical properties and associated risks. In doing so, we also respond to the points raised by Ioannidis et al. (2020). https://www.sciencedirect.com/science/article/pii/S0169207020301230 Il 21/10/2020 19:03, Enrico Nardelli ha scritto:
by John P.A. Ioannidis, Sally Cripps , and Martin A.Tanner
ABSTRACT Epidemic forecasting has a dubious track-record, and its failures became more prominent with COVID-19. Poor data input, wrong modeling assumptions, high sensitivity of estimates, lack of incorporation of epidemiological features, poor past evidence on effects of available interventions, lack of transparency, errors, lack of determinacy, consideration of only one or a few dimensions of the problem at hand, lack of expertise in crucial disciplines, groupthink and bandwagon effects, and selective reporting are some of the causes of these failures. Nevertheless, epidemic forecasting is unlikely to be abandoned. Some (but not all) of these problems can be fixed. Careful modeling of predictive distributions rather than focusing on point estimates, considering multiple dimensions of impact, and continuously reappraising models based on their validated performance may help. If extreme values are considered, extremes should be considered for the consequences of multiple dimensions of impact so as to continuously calibrate predictive insights and decision-making. When major decisions (e.g. draconian lockdowns) are based on forecasts, the harms (in terms of health, economy, and society at large) and the asymmetry of risks need to be approached in a holistic fashion, considering the totality of the evidence.
https://www.sciencedirect.com/science/article/pii/S0169207020301199#!
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===================================================================== Prof. Enrico Nardelli Dipartimento di Matematica - Universita' di Roma "Tor Vergata" Via della Ricerca Scientifica snc - 00133 Roma tel: +39 06 7259.4204 fax: +39 06 7259.4699 mobile: +39 335 590.2331 e-mail: nardelli@mat.uniroma2.it home page: http://www.mat.uniroma2.it/~nardelli blog: http://www.ilfattoquotidiano.it/blog/enardelli/ http://link-and-think.blogspot.it/ =====================================================================
-- EN ===================================================================== Prof. Enrico Nardelli Dipartimento di Matematica - Universita' di Roma "Tor Vergata" Via della Ricerca Scientifica snc - 00133 Roma tel: +39 06 7259.4204 fax: +39 06 7259.4699 mobile: +39 335 590.2331 e-mail: nardelli@mat.uniroma2.it home page: http://www.mat.uniroma2.it/~nardelli blog: http://www.ilfattoquotidiano.it/blog/enardelli/ http://link-and-think.blogspot.it/ ===================================================================== --