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Table 1 Experiment 1 (Synthetic Data).

From: Bifurcation analysis informs Bayesian inference in the Hes1 feedback loop

θ

sp1

sp2

sp3

σ

acc rate

R ^ MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGafmOuaiLbaKaaaaa@2D12@

P 0

85

95

91

0.5

26

1.0009

n

4

5

5.3

0.7

34

1.0001

μ m

0.024

0.028

0.022

0.1

43

1.0004

μ p

0.036

0.034

0.033

0.1

33

1.0000

Ï„

19

19.2

18.7

0.01

20

1.0000

  1. This table shows inputs and convergence information for 3 illustrative MCMC chains. For each parameter, θ we show the starting point (sp) of the Markov chains (columns 2–4), variance σ of the Gaussian proposal function (column 5), the acceptance rate (column 6) and statistic R ^ MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGafmOuaiLbaKaaaaa@2D12@ (column 7).