HCV DATA 
 
ML fit with estimation of theta 
 

**Iteration 1
LME step: Loglik: 16.94440 , nlm iterations: 50 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
 -0.1454266   0.6506719   1.6597137   1.3991972  -5.0662594 -10.7992468 
varStruct  parameters:
    power 
0.9694313 

PNLS step: RSS =  4.251224 
 fixed effects:1.45409  1.23954  -0.157512  
 iterations: 5 

Convergence:
      fixed    reStruct   varStruct 
 0.21012737 21.52055083  0.03153256 

**Iteration 2
LME step: Loglik: 31.31550 , nlm iterations: 22 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
-0.54784003 -0.06749765  1.70494774  0.44015416 -0.30075912 -2.00659979 
varStruct  parameters:
   power 
1.011279 

PNLS step: RSS =  3.403079 
 fixed effects:1.44972  1.24161  -0.158088  
 iterations: 4 

Convergence:
      fixed    reStruct   varStruct 
0.003643634 5.621977725 0.041380965 

**Iteration 3
LME step: Loglik: 30.98927 , nlm iterations: 16 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
-0.55224993 -0.05541547  1.70826563  0.41733233 -0.20587567 -2.09894673 
varStruct  parameters:
   power 
1.009925 

PNLS step: RSS =  3.443483 
 fixed effects:1.44945  1.23996  -0.157908  
 iterations: 3 

Convergence:
      fixed    reStruct   varStruct 
0.001330337 0.243871773 0.001340455 

**Iteration 4
LME step: Loglik: 30.95436 , nlm iterations: 15 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
-0.55116407 -0.05606632  1.70661723  0.41972085 -0.21054466 -2.07269914 
varStruct  parameters:
   power 
1.009521 

PNLS step: RSS =  3.445706 
 fixed effects:1.44941  1.23997  -0.157922  
 iterations: 2 

Convergence:
       fixed     reStruct    varStruct 
8.513316e-05 3.375163e-02 4.003256e-04 

**Iteration 5
LME step: Loglik: 30.95124 , nlm iterations: 12 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
-0.55130375 -0.05601236  1.70664803  0.41933709 -0.20892434 -2.07336150 
varStruct  parameters:
   power 
1.009537 

PNLS step: RSS =  3.445837 
 fixed effects:1.44941  1.23997  -0.157922  
 iterations: 1 

Convergence:
       fixed     reStruct    varStruct 
0.000000e+00 3.861785e-03 1.540695e-05 

**Iteration 6
LME step: Loglik: 30.95124 , nlm iterations: 2 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
-0.55130694 -0.05600465  1.70666135  0.41931801 -0.20875365 -2.07353199 
varStruct  parameters:
   power 
1.009539 

PNLS step: RSS =  3.445828 
 fixed effects:1.44941  1.23997  -0.157922  
 iterations: 1 

Convergence:
       fixed     reStruct    varStruct 
0.000000e+00 5.461421e-05 2.287021e-06 

**Iteration 7
LME step: Loglik: 30.95124 , nlm iterations: 1 
reStruct  parameters:
        id1         id2         id3         id4         id5         id6 
-0.55130650 -0.05600644  1.70666029  0.41931626 -0.20874363 -2.07350814 
varStruct  parameters:
   power 
1.009539 

PNLS step: RSS =  3.445828 
 fixed effects:1.44941  1.23997  -0.157922  
 iterations: 1 

Convergence:
       fixed     reStruct    varStruct 
0.000000e+00 2.341153e-06 0.000000e+00 

 
Nonlinear mixed-effects model fit by maximum likelihood
  Model: vl ~ meanfunc(days, b1, b2, b3) 
 Data: vdat 
        AIC      BIC   logLik
  -39.90248 1.887540 30.95124

Random effects:
 Formula: list(b1 ~ 1, b2 ~ 1, b3 ~ 1)
 Level: id
 Structure: General positive-definite, Log-Cholesky parametrization
         StdDev     Corr         
b1       0.19534581 b1     b2    
b2       0.11546963 -0.418       
b3       0.01854371 -0.117  0.352
Residual 0.10218563              

Variance function:
 Structure: Power of variance covariate
 Formula: ~fitted(.) 
 Parameter estimates:
   power 
1.009539 
Fixed effects: list(b1 ~ 1, b2 ~ 1, b3 ~ 1) 
        Value  Std.Error  DF   t-value p-value
b1  1.4494064 0.03712816 298  39.03792       0
b2  1.2399668 0.02800273 298  44.28022       0
b3 -0.1579217 0.00435219 298 -36.28560       0
 Correlation: 
   b1     b2    
b2 -0.216       
b3 -0.017  0.085

Standardized Within-Group Residuals:
        Min          Q1         Med          Q3         Max 
-2.47653290 -0.67063428 -0.01144561  0.64405378  2.62394223 

Number of Observations: 330
Number of Groups: 30 

 
D matrix 
             [,1]          [,2]          [,3]
[1,]  0.038159985 -0.0094286205 -0.0004238250
[2,] -0.009428621  0.0133332355  0.0007537148
[3,] -0.000423825  0.0007537148  0.0003438692