PopED Results 

        2018-09-10 08:27:20

==============================================================================
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)

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

Initial Sampling Schedule
Group 1:    0.5      1      2      6     24     36     72    120

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

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

Initial OFV = 55.3964

Efficiency criterion [usually defined as OFV^(1/npar)]  = 1016.94

Initial design
expected relative standard error
(%RSE, rounded to nearest integer)
    Parameter   Values   RSE_0
      bpop[1]     0.15       5
      bpop[2]        8       3
      bpop[3]        1      14
       D[1,1]     0.07      30
       D[2,2]     0.02      37
       D[3,3]      0.6      27
   SIGMA[1,1]     0.01      32
   SIGMA[2,2]     0.25      26

==============================================================================
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-family design (0) 
  (with or without parameter uncertainty)

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

* Optimize Covariates

MFEA - It. : 1
Exchanged covariate 1 in group/ind 1 from 70 to 100
Delta : 0.0114735   OFV. : 56.032
MFEA - It. : 2
Delta : 0   OFV. : 56.032
===============================================================================
FINAL RESULTS

Optimized Covariates:
Group 1: 100

 FIM: 
 1.827369e+04  8.435432e+00  4.357206e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
 8.435432e+00  1.848748e+01 -2.833403e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
 4.357206e+00 -2.833403e+00  5.067616e+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  2.641420e+03  1.601021e+00  6.674501e-03  6.989511e+02  5.461617e+01
 0.000000e+00  0.000000e+00  0.000000e+00  1.601021e+00  2.187435e+04  8.028175e+00  1.051093e+04  1.762957e+02
 0.000000e+00  0.000000e+00  0.000000e+00  6.674501e-03  8.028175e+00  4.012614e+01  6.745342e+01  1.707317e+00
 0.000000e+00  0.000000e+00  0.000000e+00  6.989511e+02  1.051093e+04  6.745342e+01  3.185460e+05  6.212224e+03
 0.000000e+00  0.000000e+00  0.000000e+00  5.461617e+01  1.762957e+02  1.707317e+00  6.212224e+03  2.971102e+02


Inverse(FIM):
 5.473692e-05 -2.591866e-05 -6.155519e-06  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
-2.591866e-05  5.457046e-02  3.053370e-03  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00
-6.155519e-06  3.053370e-03  1.990439e-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  3.801806e-04  2.604884e-07  2.166566e-06  8.829664e-07 -8.851535e-05
 0.000000e+00  0.000000e+00  0.000000e+00  2.604884e-07  4.646428e-05 -6.793999e-06 -1.679132e-06  7.529397e-06
 0.000000e+00  0.000000e+00  0.000000e+00  2.166566e-06 -6.793999e-06  2.493183e-02 -3.945778e-06 -5.713390e-05
 0.000000e+00  0.000000e+00  0.000000e+00  8.829664e-07 -1.679132e-06 -3.945778e-06  5.364143e-06 -1.113012e-04
 0.000000e+00  0.000000e+00  0.000000e+00 -8.851535e-05  7.529397e-06 -5.713390e-05 -1.113012e-04  5.705062e-03

OFV = 56.032

Efficiency criterion [usually defined as det(FIM)^(1/npar)]  = 1101.03

Efficiency: 
  ((exp(ofv_final) / exp(ofv_init))^(1/n_parameters)) = 1.0827

Expected relative standard error
(%RSE, rounded to nearest integer):
    Parameter   Values   RSE_0   RSE
      bpop[1]     0.15       5     5
      bpop[2]        8       3     3
      bpop[3]        1      14    14
       D[1,1]     0.07       0     0
       D[2,2]     0.02      37    34
       D[3,3]      0.6       0     0
   SIGMA[1,1]     0.01      32    23
   SIGMA[2,2]     0.25      26    30

Total running time: 0.069 seconds
