___________________________________________________________________
 |                                                                 |
 |                      STANDARD ERROR OF ESTIMATE                 |
 |_________________________________________________________________|

 MEANING: NONMEM's estimate of the precision of its parameter estimates
 CONTEXT: NONMEM output

 DISCUSSION:
 Asymptotic statistical theory applied to extended least-squares  esti-
 mation (as used in NONMEM) says that the distribution of the parameter
 estimators is multivariate  normal,  with  variance-covariance  matrix
 that can be estimated from the data.  NONMEM supplies such an estimate
 (See covariance matrix of estimate).  The square root of the ith diag-
 onal element of the matrix is the standard error of the ith  parameter
 estimate.  NONMEM output presents standard errors as in this example.

  ****** STANDARD ERROR OF ESTIMATE ********************

  THETA - VECTOR OF FIXED EFFECTS PARAMETERS  **********
             TH 1      TH 2
          6.27E+00  1.92E+01

  OMEGA - COV MATRIX FOR RANDOM EFFECTS - ETAS  ********

             ETA1      ETA2
  ETA1    1.71E-02
  ETA2   .........  1.12E-01

  SIGMA - COV MATRIX FOR RANDOM EFFECTS - EPSILONS  ****

             EPS1
   EPS1   5.57E-03

 Note that standard errors are given for all types of population param-
 eters:  THETA,  the  vector of fixed effects parameters, and OMEGA and
 SIGMA, the matrices of random effects parameters.   In  this  example,
 the  2x2  matrix,  OMEGA,  was constrained to be diagonal; the omitted
 entry  (.........)  indicates  that  the  element  omega(2,1)  is  not
 estimated, and consequently has no standard error.

REFERENCES: Guide I Section C.3.5.2
REFERENCES: Guide V Section 5.4.2.1


  
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