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_21
Snippet: 3. Simulation 2. We used the above weighing scheme and repeated the previous simulation. In that sense we altered the likelihood function while leaving the prior distributions intact. Everything else (including the simulation details such as number of posterior draws, thinning, etc.) was the same as reported in Section 2. Again, we observed good convergence for all parameters (see Fig. 4 depicting a traceplot and a histogram for the K parameter)......
Document: 3. Simulation 2. We used the above weighing scheme and repeated the previous simulation. In that sense we altered the likelihood function while leaving the prior distributions intact. Everything else (including the simulation details such as number of posterior draws, thinning, etc.) was the same as reported in Section 2. Again, we observed good convergence for all parameters (see Fig. 4 depicting a traceplot and a histogram for the K parameter). . 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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