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_11
Snippet: We used the blockwise Random Walk Metropolis algorithm 2 in order to sample from the joint posterior distribution of the four parameters of the model (K, A, r, and σ). The proposal distribution was multivariate normal with scaled variance-covariance matrix estimated on the basis of pilot runs. Uninformative improper uniform priors ranging from 0 to + ∞ were employed for all parameters in the model. A pilot chain showed an acceptance rate withi.....
Document: We used the blockwise Random Walk Metropolis algorithm 2 in order to sample from the joint posterior distribution of the four parameters of the model (K, A, r, and σ). The proposal distribution was multivariate normal with scaled variance-covariance matrix estimated on the basis of pilot runs. Uninformative improper uniform priors ranging from 0 to + ∞ were employed for all parameters in the model. A pilot chain showed an acceptance rate within the optimal range of 23% (e.g. Chib & Greenberg, 1995 . 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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