Re: Fault 1009

Dear Gustavo,

re:

 Source Model terms Gamma Component Comp/SE %
C
 Variance 3830 1784 1.00000 5815.70 29.87 0
P
 leg(acm,1).anim UnStruct 1 0.161400 938.653 29.87 0
B
 leg(acm,1).anim UnStruct 1 0.811210E-01 471.776 29.87 0
B
 leg(acm,1).anim UnStruct 2 0.416000E-01 241.933 29.87 0
B
 ide(anim).leg(acm,1)UnStruct 1 0.533402 3102.11 29.87 0
B
 ide(anim).leg(acm,1)UnStruct 1 0.250886 1459.08 29.87 0
B
 ide(anim).leg(acm,1)UnStruct 2 0.120400 700.210 29.87 0
B

Covariance/Variance/Correlation Matrix UnStructured
 0.1614 0.9900
 0.8112E-01 0.4160E-01
 Covariance/Variance/Correlation Matrix UnStructured
 0.5334 0.9900
 0.2509 0.1204

When you ran the two simpler models forcing one of the correlations to
zero, I expect it moved varaition
away from that component to the other component which then became positive
definite.

These results suggest that both components are trying to move out of the
parameter space.

You could try using
2 0 CORUH .99 .1614 .0416 !GP
and
2 0 CORUH .99 .5334 .1204 !GP

in place of the two US structures.

This will confirm whether both want to go to the boundary, and if so, will
find it easier
to get the best estimates of the variances, after fixing the correlation
at .999.

As I suggested, it is not unusual with small data sets to have values on
the boundary.

May you know Jesus Christ and His blessing in 2007,

Arthur Gilmour, His servant .

PS My Mixed Model Regression Mapping paper is now available at
http://dx.doi.org/10.1016/j.csda.2006.12.031

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Received on Tue Feb 09 2007 - 09:26:41 EST