Table 1 The estimates of variance components and broad-sense heritabilities for the learning and adapted phases from the MCMC analyses of the two simulated data sets

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

 

Learning phase

Adapted phase

REML

True

 

Mean

Median

Mode

Mean

Median

Mode

  

Bimodal data

 σ a 2

672.57

607.73

573.67

721.49

695.87

679.37

752.99

800

 σ d 2

545.93

510.21

453.20

493.10

522.30

675.40

716.00

600

 σ e 2

3107.70

3143.70

3013.70

3132.10

3105.00

3020.20

2882.60

3025

 h 2

0.28

0.26

0.25

0.27

0.28

0.30

0.33

0.31

Unimodal data

 σ a 2

873.36

820.90

879.80

751.20

744.53

779.80

781.28

800

 σ d 2

619.36

642.23

658.70

591.50

585.77

579.80

571.68

600

 σ e 2

2845.40

2865.00

2894.70

2965.00

2971.90

2960.90

2928.79

3025

 h 2

0.34

0.33

0.34

0.33

0.31

0.31

0.31

0.31

  1. Abbreviations: MCMC, Markov chain Monte Carlo; REML, residual maximum likelihood.
  2. REML estimates and true simulated values are also shown. The names ‘unimodal data’ and ‘bimodal data’ are based on the characteristics that these data sets exhibited during the MCMC analysis.
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