PopED Optimization Results for the Adaptive Random Search Algorithm 

        2015-12-28 09:16:32

==============================================================================
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: 1
Number of model covariates: 0

Initial Sampling Schedule
   0.5      1      2      6     24     36     72    120

Discrete Variables  (possible vales):
Group 1: 70 ( 10  20  30  40  50  60  70  80  90  100 )

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

Initial OFV = 55.3964

Efficiency criterion [usually defined as OFV^(1/npar)]  = 1.65172

Initial design expected parameter 
relative standard error (%RSE)
    Parameter   Values   RSE_0
      bpop[1]     0.15    5.10
      bpop[2]     8.00    3.03
      bpop[3]     1.00   14.26
       D[1,1]     0.07   29.76
       D[2,2]     0.02   36.68
       D[3,3]     0.60   26.75
   SIGMA[1,1]     0.01   32.01
   SIGMA[2,2]     0.25   25.64

==============================================================================
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: 1
  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 Discrete variables

*******************************
Initial Value
 OFV(mf) = 55.3964
*******************************

RS - It. : 3   OFV : 55.3964

*******************************
RS Results
 OFV(mf) = 55.3964


Optimized Discrete Variables:
Group 1: 70

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

===============================================================================
FINAL RESULTS

Optimized Discrete Variables:
Group 1: 70

 FIM: 
 1.714184e+04  2.083837e+01  1.001100e+01  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
 2.083837e+01  1.726805e+01 -3.423641e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
 1.001100e+01 -3.423641e+00  4.986470e+01  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
 0.000000e+00  0.000000e+00  0.000000e+00  2.324341e+03  9.770352e+00  3.523364e-02  7.268410e+02  9.062739e+01
 0.000000e+00  0.000000e+00  0.000000e+00  9.770352e+00  1.908388e+04  1.172132e+01  9.656159e+03  2.664871e+02
 0.000000e+00  0.000000e+00  0.000000e+00  3.523364e-02  1.172132e+01  3.885138e+01  6.478096e+01  2.947285e+00
 0.000000e+00  0.000000e+00  0.000000e+00  7.268410e+02  9.656159e+03  6.478096e+01  1.928402e+05  6.659570e+03
 0.000000e+00  0.000000e+00  0.000000e+00  9.062739e+01  2.664871e+02  2.947285e+00  6.659570e+03  4.755001e+02


Inverse(FIM):
 5.843639e-05 -7.384993e-05 -1.680231e-05  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
-7.384993e-05  5.880293e-02  4.052154e-03  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
-1.680231e-05  4.052154e-03  2.033586e-02  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
 0.000000e+00  0.000000e+00  0.000000e+00  4.340080e-04  2.022781e-07  4.408771e-06  2.351284e-06 -1.157906e-04
 0.000000e+00  0.000000e+00  0.000000e+00  2.022781e-07  5.382097e-05 -1.201761e-05 -3.198122e-06  1.466374e-05
 0.000000e+00  0.000000e+00  0.000000e+00  4.408771e-06 -1.201761e-05  2.575763e-02 -5.340956e-06 -7.895607e-05
 0.000000e+00  0.000000e+00  0.000000e+00  2.351284e-06 -3.198122e-06 -5.340956e-06  1.024750e-05 -1.421431e-04
 0.000000e+00  0.000000e+00  0.000000e+00 -1.157906e-04  1.466374e-05 -7.895607e-05 -1.421431e-04  4.108160e-03

OFV = 55.3964

Efficiency criterion [usually defined as OFV^(1/npar)]  = 1.65172

Efficiency [typically: (OFV_final/OFV_initial)^(1/npar)]: 1

Expected parameter 
relative standard error (%RSE):
    Parameter   Values   RSE_0     RSE
      bpop[1]     0.15    5.10    5.10
      bpop[2]     8.00    3.03    3.03
      bpop[3]     1.00   14.26   14.26
       D[1,1]     0.07   29.76   29.76
       D[2,2]     0.02   36.68   36.68
       D[3,3]     0.60   26.75   26.75
   SIGMA[1,1]     0.01   32.01   32.01
   SIGMA[2,2]     0.25   25.64   25.64

Total running time: 0.051 seconds
