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Table 2 Performance of three sampling algorithms in calculating the marginal likelihood of an analytically tractable example

From: BCM: toolkit for Bayesian analysis of Computational Models using samplers

Dimensions

Log marginal likelihood

Likelihood evaluations (x1000)

Analytical

FOPTMC

SMC

MultiNest

FOPTMC

SMC

MultiNest

2

−1.75

−1.80 ± 0.68

−1.74 ± 0.39

−1.73 ± 0.29

147

79

18

5

−5.67

−5.98 ± 1.65

−5.66 ± 0.47

−5.73 ± 0.38

287

281

28

10

−14.59

−14.92 ± 3.34

−14.64 ± 0.62

−14.13 ± 0.63

969

521

95

30

−60.13

−61.11 ± 9.10

−59.85 ± 0.97

*

6420

1511

*

100

−255.62

−257.7 ± 24.8

−255.8 ± 1.54

*

96,251

4271

*

  1. The following algorithms were used: FOPTMC feedback-optimized parallel-tempered Markov Chain Monte Carlo [12], SMC automated-temperature sequential Monte Carlo but without ABC approximation [15], and MultiNest [5]. The column ‘Analytical’ gives the marginal likelihood value calculated analytically. (*) indicates that the computation time exceeded the maximal time of 1 h; the other calculations required at most 5 min
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BMC Systems Biology

ISSN: 1752-0509

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