Author: Svetoslav Bliznashki
Title: A Bayesian Logistic Growth Model for the Spread of COVID-19 in New York Document date: 2020_4_7
ID: lhv83zac_29
Snippet: The results indicated good convergence (a traceplot for the K parameter is shown in Fig. 6 below; histograms from the posterior for all parameters are shown in Appendix A). Table 5 gives the point and interval estimates for the posteriors for the five parameters in question. We see that the estimates differ substantially from the ones reported above and that a steeper curve is indicated. The lognormal distribution is not symmetric and hence we us.....
Document: The results indicated good convergence (a traceplot for the K parameter is shown in Fig. 6 below; histograms from the posterior for all parameters are shown in Appendix A). Table 5 gives the point and interval estimates for the posteriors for the five parameters in question. We see that the estimates differ substantially from the ones reported above and that a steeper curve is indicated. The lognormal distribution is not symmetric and hence we use the actual Metropolis-Hastings acceptance probability (e.g. Chib & Greenberg, 1995) during the step sampling from the df posterior. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
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