Dear Nagal,
You have a small amount of data so convergence was difficult.
The following job has 3 parts.
Part 1 gets a reasonable estimate
of the error variance.
PART 2 notes the high correlation so
gets a smoother genetic matrix.
LogL=-840.974 S2= 1.0000 1203 df
Source Model terms Gamma Component Comp/SE % C
Residual UnStruct 1 3.23510 3.23510 5.28 0 U
Residual UnStruct 1 2.82548 2.82548 4.63 0 U
Residual UnStruct 2 3.35958 3.35958 5.35 0 U
Residual UnStruct 1 2.66142 2.66142 4.39 0 U
Residual UnStruct 2 3.12695 3.12695 5.03 0 U
Residual UnStruct 3 3.45187 3.45187 5.49 0 U
Tr.id CORRelat 3 1.00205 1.00205 118.14 0 U
Tr.id CORRelat 3 2.08741 2.08741 2.74 0 U
Covariance/Variance/Correlation Matrix UnStructured
3.235 0.8570 0.7964
2.825 3.360 0.9182
2.661 3.127 3.452
Analysis of Variance DF F-incr
14 Tr.yearb 12 79.46
15 Tr.breed 3 30.16
16 Tr.sex 3 17.66
17 Tr.tyb 3 15.71
18 Tr.aod 12 3.21
Note that the genetic correaltion is estimated GT 1
so given the error variance are uniform, there may be
no gain in having separate variance for the 3 times of measurement.
I.E. maybe the model should just fit id not Tr.id
Anyway, !PART 3 gives
LogL=-839.673 S2= 1.0000 1203 df
Source Model terms Gamma Component Comp/SE % C
Residual UnStruct 1 3.43347 3.43347 5.59 0 U
Residual UnStruct 1 2.82459 2.82459 4.62 0 U
Residual UnStruct 2 3.11536 3.11536 4.75 0 U
Residual UnStruct 1 2.72358 2.72358 4.57 0 U
Residual UnStruct 2 2.96266 2.96266 4.67 0 U
Residual UnStruct 3 3.37582 3.37582 5.24 0 U
Tr.id UnStruct 1 1.82947 1.82947 2.48 1 U
Tr.id UnStruct 1 2.09764 2.09764 2.74 0 U
Tr.id UnStruct 2 2.40448 2.40448 2.88 0 U
Tr.id UnStruct 1 2.01612 2.01612 2.73 0 U
Tr.id UnStruct 2 2.30970 2.30970 2.87 0 U
Tr.id UnStruct 3 2.19816 2.19816 2.75 0 U
Covariance/Variance/Correlation Matrix UnStructured
3.433 0.8636 0.8000
2.825 3.115 0.9136
2.724 2.963 3.376
Covariance/Variance/Correlation Matrix UnStructured
1.829 1.000 1.005
2.098 2.404 1.005
2.016 2.310 2.198
A few more runs are required. I hope this gets you going.
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Arthur Gilmour PhD mailto:Arthur.Gilmour@agric.nsw.gov.au
Principal Research Scientist (Biometrics) fax: <61> 2 6391 3899
NSW Agriculture <61> 2 6391 3922
Orange Agricultural Institute telephone work: <61> 2 6391 3815
Forest Rd, ORANGE, 2800, AUSTRALIA home: <61> 2 6362 0046
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