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Table 3.
Prior selected for each parameter of the Bayesian analysis using a hierarchical partial pooling model.
| Parameter | Range | Type |
|---|---|---|
| Ti | – | δ(Ti – Tmodel) |
| vi | – | δ(vi – vmodel) |
| μO | [8.40, 9.10] | Uniform |
| σO | σ = 1 | Half normal |
| log(ϵO) | [8.40, 9.10] | Bounded normal μ = μO; σ = σO |
| log(ϵNi) | [5.80, 6.36] | Bounded normal μ = 6.17; σ = 0.05 (a) |
| v(ws) [Å] | [−0.2, 0.2] | Bounded normal μ = 0; σ = 0.1 |
| c factor | – | Normal μ = 1; σ = 0.2 |
| log(s) | [−3, 6] | Uniform |
Notes.
(a)
Taking into account (Scott et al. 2009).
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