Table 4 Results of Markov chain Monte Carlo fitting of single-compartment models with homocysteine as an unobserved intermediate metabolite, created at a rate depending on SAHH (λ) and removed at a rate depending on CBS (μ), applied to the simulation taking homocysteine concentration as the causal variable

Linear:

λ, μ fixed

λ, μ random

Michaelis-Menten:

λ, μ fixed: ln(μ₀/λ₀)

ln[V _max (1)/V _max (0)]

$\mathsf{\text{ln}}\left(K_m^{\mu }/K_m^{\lambda }\right)$

γs random: ln(μ₀/λ₀) ln[V _max (1)/V _max (0)] $\mathsf{\text{ln}}\left({}_m^{\mu }/K_m^{\lambda }\right)$

Stochastic differential equations:

N = 10 fixed

$N~\Gamma \left(100,1\right):\widehat{N}=116$