From: <fmujibi_at_UALBERTA.CA>

Date: Tue, 26 May 2009 12:50:44 -0600

Date: Tue, 26 May 2009 12:50:44 -0600

Hello All.

I am wondering about the validity of the variance components obtained

when parameters converge at the boundary. (ASreml gives a warning

message "? - liable to change from P to B"). Despite the fact that

standard errors are not obtained, do the estimates still stand?

Attached is a truncated version of the .asr file that I get

Folder: C:\Documents and Settings\User\Desktop\Final_Formats

id !P

sire !P

dam !P

breed 4 !I

group 3 !I

A-inverse retrieved from ainverse.bin

PEDIGREE [testdata.csv ] has 1014 identities, 2433 Non zero elements

QUALIFIERS: !SKIP 1 !EXTRA 90 !MAXIT 100 !MVINCLUDE

Reading testdata.csv FREE FORMAT skipping 1 lines

Bivariate analysis of vfa and fwd100

Using 512 records of 512 read

Model term Size #miss #zero MinNon0 Mean MaxNon0

1 id !P 1014 0 0 1.000 491.3 1014.

2 sire !P 1014 33 0 1.000 235.3 1013.

3 dam !P 1014 40 0 34.00 438.9 1010.

4 breed 4 33 0 1 2.6931 4

5 group 3 33 0 1 2.1315 3

6 age 33 0 161.0 240.5 332.0

Warning: Fewer levels found in vfa than specified

7 vfa 50 33 2 -3 0.0082 3

8 stpws50 0 0 -2.486 0.9287 5.230

9 fwd100 Variate 0 0 -3.493 1.972 9.896

10 bwd50 17 0 -1.833 0.2840 2.468

11 st50blp 17 0 -2.578 0.2707 3.205

12 Trait 2

13 at(Trait,1) 1

14 at(Trait,1).age 1 13 at(Trait,1: 1 6 age : 1

15 at(Trait,1).breed 4 13 at(Trait,1: 1 4 breed : 4

16 at(Trait,1).group 3 13 at(Trait,1: 1 5 group : 3

17 Trait.sire 2028 12 Trait : 2 2 sire : 1014

Warning: 330 missing values were detected in the design variables

Missing values are treated as zeros

Consider deleting the records in which they occur

512 identity

2 UnStructure 0.7900 0.4000 2.1000

1024 records assumed pre-sorted 2 within 512

2 UnStructure 0.0800 0.2000 2.8500

1014 Ainverse

Structure for Trait.sire has 2028 levels defined

Forming 2038 equations: 10 dense.

Initial updates will be shrunk by factor 0.100

Notice: Algebraic ANOVA Denominator DF calculation is not available

Numerical derivatives will be used.

Notice: 2 singularities detected in design matrix.

1 LogL=-697.455 S2= 1.0000 983 df

2 LogL=-687.781 S2= 1.0000 983 df

3 LogL=-666.246 S2= 1.0000 983 df

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

4 LogL=-654.848 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

5 LogL=-653.056 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

6 LogL=-653.028 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

7 LogL=-653.016 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

8 LogL=-653.005 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

9 LogL=-652.996 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

10 LogL=-652.988 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

11 LogL=-652.981 S2= 1.0000 983 df : 3 components constrained

Notice: US matrix updates modified 1 time(s) to keep them positive definite.

12 LogL=-652.975 S2= 1.0000 983 df : 3 components constrained

13 LogL=-652.969 S2= 1.0000 983 df : 3 components constrained

14 LogL=-652.964 S2= 1.0000 983 df : 3 components constrained

15 LogL=-652.960 S2= 1.0000 983 df : 3 components constrained

41 LogL=-652.921 S2= 1.0000 983 df : 3 components constrained

Notice: US structures were modified 38 times to make them positive definite.

If ASReml has fixed the structure [flagged by B], it may not have

converged to a maximum likelihood solution.

!EMFLAG 0 Single standard EM update when AI update unacceptable

Source Model terms Gamma Component Comp/SE % C

Residual UnStructured 1 1 0.827632 0.827632 15.03 0 P

Residual UnStructured 2 1 0.883629 0.883629 11.06 0 P

Residual UnStructured 2 2 2.15469 2.15469 13.76 0 P

Trait.sire UnStructured 1 1 0.603739E-01 0.603739E-01 0.00 0 ?

Trait.sire UnStructured 2 1 0.393079 0.393079 0.00 0 ?

Trait.sire UnStructured 2 2 3.22522 3.22522 0.00 0 ?

Warning: Code B - fixed at a boundary (!GP) F - fixed by user

? - liable to change from P to B P - positive definite

C - Constrained by user (!VCC) U - unbounded

S - Singular Information matrix

S means there is no information in the data for this parameter.

Very small components with Comp/SE ratios of zero sometimes indicate poor

scaling. Consider rescaling the design matrix in such cases.

Covariance/Variance/Correlation Matrix UnStructured Residual

0.8276 0.6617

0.8836 2.155

Covariance/Variance/Correlation Matrix UnStructured Trait.sire

0.6037E-01 0.8908

0.3931 3.225

Analysis of Variance NumDF DenDF F_inc Prob

12 Trait 2 NA 149.34 NA

14 at(Trait,1).age 1 496.8 0.27 0.605

15 at(Trait,1).breed 3 735.8 3.16 0.026

16 at(Trait,1).group 2 473.3 4.34 0.015

Notice: The DenDF values are calculated ignoring fixed/boundary/singular

variance parameters using numerical derivatives.

17 Trait.sire 2028 effects fitted ( 740 are zero)

-- Denis Fidalis Mujibi 1430 College Plaza 8215 112 St, Edmonton T6G 2C5, AB, Canada. fmujibi_at_ualberta.caReceived on Wed May 26 2009 - 12:50:44 EST

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