Selected article for: "Bayes factor and richards model"
Author: Liu, Wendi; Tang, Sanyi; Xiao, Yanni
Title: Model Selection and Evaluation Based on Emerging Infectious Disease Data Sets including A/H1N1 and Ebola
  • Document date: 2015_9_15
    • ID: 0j4is0n4_47
    Snippet: The above results show that the proposed model selection methods based on Bayes factor and MCMC method can help us to choose the optimal model. In Figure 1 , we plot the fitting results for four models based on the simulated time series generated from Richards model and Gompertz model. Although the other three models can also fit the simulated data well, it is obvious that the fitting of the Richards model and data time points is the best for tim.....
    Document: The above results show that the proposed model selection methods based on Bayes factor and MCMC method can help us to choose the optimal model. In Figure 1 , we plot the fitting results for four models based on the simulated time series generated from Richards model and Gompertz model. Although the other three models can also fit the simulated data well, it is obvious that the fitting of the Richards model and data time points is the best for time series Computational and Mathematical Methods in Medicine 5 Province exhibited the bimodality, where the first and small wave started around 3 September till 21 September and the second and large wave followed [11, 13] . In order to evaluate the effectiveness of control measures on A/H1N1, Tang et al. [11, 13] proposed the compartment epidemic models and then employed the A/H1N1 data sets to estimate the unknown parameters.

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