Author: Ignazio Ciufolini; Antonio Paolozzi
Title: Prediction of the time evolution of the Covid-19 Pandemic in Italy by a Gauss Error Function and Monte Carlo simulations Document date: 2020_3_30
ID: ltcfsrb2_11
Snippet: The second step was to generate a random matrix × , where (columns) is the number of days and (rows) is a number of outcomes that we have chosen to be 150. Each number in the matrix is part of a Gaussian distribution with mean equal to 1 and sigma equal to 0.1 (i.e., 10% of 1), either row-wise and column-wise. In such a way each day is characterized by 150 simulated outcomes that allow to apply a statistical approach. The 150 outcomes represent .....
Document: The second step was to generate a random matrix × , where (columns) is the number of days and (rows) is a number of outcomes that we have chosen to be 150. Each number in the matrix is part of a Gaussian distribution with mean equal to 1 and sigma equal to 0.1 (i.e., 10% of 1), either row-wise and column-wise. In such a way each day is characterized by 150 simulated outcomes that allow to apply a statistical approach. The 150 outcomes represent a reasonably large number of simulated deviations from the official data according to the Central Limit theorem.
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