This is an REML analysis.
1is fixed effect number 1of factor 1
1is fixed effect number 1of factor 2
2is fixed effect number 2of factor 2
3is fixed effect number 3of factor 2
4is fixed effect number 4of factor 2
5is fixed effect number 5of factor 2
6is fixed effect number 6of factor 2
2is fixed effect number 2of factor 1
At iteration 0
The current parameter values:
Additive, population 1:
0.000
Additive, population 2:
0.000
Environmental, population 1:
1.000
Environmental, population 2:
1.000
Dominance, population 1:
0.000
Dominance, population 2:
0.000
LogLike -796.7258
At iteration 1
The current parameter values:
Additive, population 1:
0.109
Additive, population 2:
0.252
Environmental, population 1:
2.728
Environmental, population 2:
1.212
Dominance, population 1:
0.441
Dominance, population 2:
1.930
LogLike -524.9395
At iteration 2
The current parameter values:
Additive, population 1:
0.076
Additive, population 2:
0.180
Environmental, population 1:
2.686
Environmental, population 2:
1.298
Dominance, population 1:
0.512
Dominance, population 2:
1.893
LogLike -524.9174
At iteration 3
The current parameter values:
Additive, population 1:
0.084
Additive, population 2:
0.204
Environmental, population 1:
2.689
Environmental, population 2:
1.307
Dominance, population 1:
0.502
Dominance, population 2:
1.864
LogLike -524.9164
At iteration 4
*** The unconstrained analysis converged with the following results ***
The log likelihood is -524.9164
The mean of each trait is
7.646945
The effect of the fixed factors is
(in the order given, levels within factors)
Factor: 1 Level: 1 Label: 1
has fixed factor effect 0
Factor: 1 Level: 2
Label: 2
has fixed factor effect -0.928549
Factor: 2 Level: 1 Label: 1
has fixed factor effect 0
Factor: 2 Level: 2
Label: 2
has fixed factor effect 0.017682
Factor: 2 Level: 3
Label: 3
has fixed factor effect -0.170606
Factor: 2 Level: 4
Label: 4
has fixed factor effect -0.628740
Factor: 2 Level: 5
Label: 5
has fixed factor effect -3.271790
Factor: 2 Level: 6
Label: 6
has fixed factor effect -3.474568
7.64694
-0.92855
0.01768
-0.17061
-0.62874
-3.27179
-3.47457
additive genetic components for population 1
0.0844
additive genetic components for population 2
0.2044
environmental components for population 1
2.6894
environmental components for population 2
1.3071
dominance components for population 1
0.5016
dominance components for population 2
1.8636
Large-sample var-cov matrix of the estimates
0.060846 -0.000000 0.026573 0.000000 -0.075973 -0.000000
0.286971 0.000000 0.112149 -0.000000 -0.340986
0.298556 -0.000759 -0.274670 0.000212
0.769034 0.000211 -0.963707
0.376394 -0.000059
1.473091
The test statistic comparing two likelihoods is given by twice
their difference and is compared to Chi-square with df given by the
number of parameters specified by the hypothesis.