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. 2011 Sep 16;6(9):e24833. doi: 10.1371/journal.pone.0024833

Table 1. Description of prior distributions and hyper-parameters for model parameters.

Model Parameter Prior Distribution Description
HMM1,2 μ1 Normal(0,0.01)* Mean state 1
HMM1,2 μ2 Normal(0,0.01)* Mean state 2
HMM1,2 PInit Dirichlet(0.5,0.5) Initial Probability
HMM1,2 P Beta(0.5,0.5) Probability transition matrix
HMM1,2 Y Poisson(Inline graphic) Observed count data
HMM2 X Normal(0,0.001)* Covariate coefficients

*Parameterized as mean and precision (1/variance, as in WinBUGS). For disease-level models, a Normal(0,10) prior was used to accommodate very small expected counts.