PopED Optimization Results for the Adaptive Random Search Algorithm 

        2016-10-19 08:13:47

==============================================================================
Model description : PopED model 

Model Sizes : 
Number of individual model parameters                  g[j]    : Ng    = 5
Number of population model fixed parameters            bpop[j] : Nbpop = 4
Number of population model random effects parameters   b[j]    : Nb    = 3

Typical Population Parameters:
bpop[1]:  0.15 
bpop[2]:     8 
bpop[3]:     1 
bpop[4]:     1 

Between Subject Variability matrix D (variance units) 
0.07 0.00 0.00
0.00 0.02 0.00
0.00 0.00 0.60

Diagonal Elements of D [sqrt(param)]:
D[1,1]:  0.07 [0.2646] 
D[2,2]:  0.02 [0.1414] 
D[3,3]:   0.6 [0.7746] 

Residual Unexplained Variability matrix SIGMA (variance units) : 
0.01 0.00
0.00 0.25

Diagonal Elements of SIGMA [sqrt(param)]:
SIGMA[1,1]:  0.01 [  0.1] 
SIGMA[2,2]:  0.25 [  0.5] 

==============================================================================
Experiment description (design and design space)

Numer of individuals: 32
Number of groups (individuals with same design): 1
Numer of individuals per group:
     Group 1: 32
Numer of samples per group:
 Number of discrete experimental variables: 0
Number of model covariates: 1

Initial Sampling Schedule
   0.5      1      2      6     24     36     72    120

Minimum allowed sampling values
  0.01   0.01   0.01   0.01   0.01   0.01   0.01   0.01

Maximum allowed sampling values
   120    120    120    120    120    120    120    120

Covariates  (min, max):
Group 1: 70 (0.01, 100)

===============================================================================
Initial design evaluation

Initial OFV = 57.0828

Efficiency criterion [usually defined as OFV^(1/npar)]  = 1255.57

Initial design expected parameter 
relative standard error (%RSE)
    Parameter   Values   RSE_0
      bpop[1]     0.15    4.84
      bpop[2]     8.00    2.96
      bpop[3]     1.00    6.59
       D[1,1]     0.07   30.20
       D[2,2]     0.02   37.10
       D[3,3]     0.60   27.62
   SIGMA[1,1]     0.01   32.87
   SIGMA[2,2]     0.25   26.03

==============================================================================
Optimization Settings

Random Search :
Number of cycles : 3
Locality factor for xt : 10
Locality factor for a  : 10

==============================================================================
Criterion Specification

OFV calculation for FIM: 4 
  1=Determinant of FIM,
  4=log determinant of FIM,
  6=determinant of interesting part of FIM (Ds)

Approximation method: 0
  0=FO, 
  1=FOCE, 
  2=FOCEI, 
  3=FOI

Fisher Information Matrix type: 0
  0=Full FIM,
  1=Reduced FIM,
  2=weighted models,
  3=Loc models,
  4=reduced FIM with derivative of SD of sigma as pfim,
  5=FULL FIM parameterized with A,B,C matrices & derivative of variance,
  6=Calculate one model switch at a time, good for large matrices,
  7=Reduced FIM parameterized with A,B,C matrices & derivative of variance

Design family: 1
  D-family design (1) or 
  ED-familty design (0) 
  (with or without parameter uncertainty)

==============================================================================
Optimization of design parameters

* Optimize Sampling Schedule
* Optimize Covariates

*******************************
Initial Value
 OFV(mf) = 57.0828
*******************************

RS - It. : 3   OFV : 57.0828

*******************************
RS Results
 OFV(mf) = 57.0828

Optimized Sampling Schedule
   0.5      1      2      6     24     36     72    120

Optimized Covariates:
Group 1: 70

*********************************

===============================================================================
FINAL RESULTS
Optimized Sampling Schedule
   0.5      1      2      6     24     36     72    120

Optimized Covariates:
Group 1: 70

 FIM: 
 1.986500e+04  1.431549e+00  1.101612e+01 -7.085972e+02 -1.875499e+03  4.619271e+00 -4.227062e+03 -4.701628e+02
 1.431549e+00  2.067982e+01 -6.826283e+00 -2.926098e+01 -8.632137e+01 -6.135483e+00 -4.735604e+02 -1.119385e+01
 1.101612e+01 -6.826283e+00  2.391996e+02 -2.164590e-01 -7.106564e+01  1.300806e+01  7.167044e+02  3.670295e+01
-7.085972e+02 -2.926098e+01 -2.164590e-01  2.324341e+03  9.770352e+00  3.523364e-02  7.268410e+02  9.062739e+01
-1.875499e+03 -8.632137e+01 -7.106564e+01  9.770352e+00  1.908388e+04  1.172132e+01  9.656159e+03  2.664871e+02
 4.619271e+00 -6.135483e+00  1.300806e+01  3.523364e-02  1.172132e+01  3.885138e+01  6.478096e+01  2.947285e+00
-4.227062e+03 -4.735604e+02  7.167044e+02  7.268410e+02  9.656159e+03  6.478096e+01  1.928402e+05  6.659570e+03
-4.701628e+02 -1.119385e+01  3.670295e+01  9.062739e+01  2.664871e+02  2.947285e+00  6.659570e+03  4.755001e+02


Inverse(FIM):
 5.262233e-05  4.084226e-05 -5.839093e-06  1.435819e-05  5.071977e-06 -2.224067e-06 -1.327247e-06  6.646717e-05
 4.084226e-05  5.600404e-02  9.087621e-04  7.166204e-04  1.898377e-04  8.301367e-03  1.660120e-04 -1.330852e-03
-5.839093e-06  9.087621e-04  4.341708e-03  2.123368e-05  2.728146e-05 -1.288375e-03 -7.010881e-06 -2.326690e-04
 1.435819e-05  7.166204e-04  2.123368e-05  4.468471e-04  3.994183e-06  1.047293e-04  4.068689e-06 -1.156094e-04
 5.071977e-06  1.898377e-04  2.728146e-05  3.994183e-06  5.506955e-05  7.177755e-06 -2.827935e-06  1.531593e-05
-2.224067e-06  8.301367e-03 -1.288375e-03  1.047293e-04  7.177755e-06  2.745822e-02  2.274821e-05 -2.201027e-04
-1.327247e-06  1.660120e-04 -7.010881e-06  4.068689e-06 -2.827935e-06  2.274821e-05  1.080207e-05 -1.474820e-04
 6.646717e-05 -1.330852e-03 -2.326690e-04 -1.156094e-04  1.531593e-05 -2.201027e-04 -1.474820e-04  4.235760e-03

OFV = 57.0828

Efficiency criterion [usually defined as det(FIM)^(1/npar)]  = 1255.57

Efficiency: 
  ((exp(ofv_final) / exp(ofv_init))^(1/n_parameters)) = 1

Expected parameter 
relative standard error (%RSE):
    Parameter   Values   RSE_0     RSE
      bpop[1]     0.15    4.84    4.84
      bpop[2]     8.00    2.96    2.96
      bpop[3]     1.00    6.59    6.59
       D[1,1]     0.07   30.20   30.20
       D[2,2]     0.02   37.10   37.10
       D[3,3]     0.60   27.62   27.62
   SIGMA[1,1]     0.01   32.87   32.87
   SIGMA[2,2]     0.25   26.03   26.03

Total running time: 0.074 seconds
