+--------------------------------------------------------------------+
 |                                                                    |
 |                   CORRELATION MATRIX OF ESTIMATE                   |
 |                                                                    |
 +--------------------------------------------------------------------+

 MEANING:  Part  of 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
 of  the  variance-covariance  matrix  of   the   parameter   estimates
 (See covariance matrix of estimate).   The  correlation  matrix is the
 variance-covariance matrix in correlation form.   If  the  correlation
 between  two  parameters  is large (e.g., >.95), then one may conclude
 that a considerable portion of the uncertainty in  each  parameter  is
 due  to the inability of the data to distinguish between the two.  The
 problem can be avoided by getting additional data or by using  a  sim-
 pler (fewer parameters) model.

 **************** CORRELATION MATRIX OF ESTIMATE ********************
             TH 1      TH 2      OM11      OM12      OM22      SG11
  TH 1        1.01E+00
  TH 2       -2.85E-01  2.55E-02
  OM11        8.87E-01 -6.77E-01  1.67E+01
  OM12       ......... ......... ......... .........
  OM22        2.81E-01 -9.96E-01  6.72E-01 .........  1.31E-03
  SG11       -4.83E-01  3.10E-01 -5.44E-01 ......... -2.67E-01  1.60E-01

 The matrix (which is symmetric) is given in lower triangular form.  In
 this example, the 2x2 matrix, OMEGA, was constrained to  be  diagonal;
 the  omitted entries above (.........) indicate that omega(2,1) is not
 estimated, and consequently has no  corresponding  row/column  in  the
 correlation matrix of the estimates.

 With  NONMEM  7.2  and  higher, the diagonal elements are equal to the |
 square root of the diagonal elements of the covariance  matrix  (stan- |
 dard error); with previous versions they were 1.0.

 When the size of the array exceeds 75x75, a compressed form is printed
 in which the omitted entries (.........) are not  printed.   The  com-
 pressed  form  may  also  be  requested  for arrays smaller than 75x75
 (See $covariance).

REFERENCES: Guide I Section C.3.5.2
REFERENCES: Guide V Section 5.4


  
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