Table 7 Efficiencies of two MCMC algorithms based on 10 simulation replicates

From: Bayesian adaptive Markov chain Monte Carlo estimation of genetic parameters

 

Learning phase

Adapted phase

ESS ratio

 

Avg

Min

Max

Avg

Min

Max

Avg

Min

Max

σ a 2

17.96

10.01

22.66

185.34

162.67

236.52

10.31

16.25

10.46

σ d 2

17.08

8.09

24.64

231.32

136.18

318.08

13.54

16.83

12.90

σ e 2

34.17

20.29

44.88

231.02

175.47

276.06

6.76

8.64

6.15

  1. Abbreviations: ESS, effective sample size; MCMC, Markov chain Monte Carlo.
  2. Average, minimum and maximum values of ESS are calculated for variance components from the analyses of 10 simulated data sets. Each MCMC analysis was run for 3000 iterations. In addition, the ESS ratio (adapted phase/learning phase) for the 10 simulation replicates is also given.
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