+--------------------------------------------------------------------+
 |                                                                    |
 |                   MINIMUM VALUE OF OBJ. FUNCTION                   |
 |                                                                    |
 +--------------------------------------------------------------------+

 MEANING: The value of the objective function
 CONTEXT: NONMEM output

 DISCUSSION:
 The  NONMEM  OBJECTIVE  FUNCTION  is  a goodness of fit statistic; the
 lower the value, the better the fit.  Negative values are possible and
 have   no   special  significance.   Under  certain  assumptions,  the
 (default) objective function value is minus twice the log likelihood.

 A page with the title MINIMUM VALUE OF OBJECTIVE FUNCTION" is  printed
 as part of every NONMEM output, as in this example.

 ******       MINIMUM VALUE OF OBJECTIVE FUNCTION        ***********
 *****************         11.570     ******************************

 If  the  Estimation  Step  was  NOT run, then the value printed is the
 value of the objective function using the initial parameter  estimates
 specified for the problem.

 If the Estimation Step WAS run, then the value printed is the value of
 the objective function with the final parameter estimates.

 Differences in the objective function of fits  of  the  same  data  to
 hierarchical  models can often be used to test approximately the plau-
 sibility of the smaller (fewer free parameters) model  by  referencing
 the  difference  to  a chi-square distribution with degrees of freedom
 equal to the difference in the number of free model parameters between
 models (hypothesis tests).

 Sometimes NM-TRAN may generate this warning message:                   |

 (WARNING   68) THE INTEGER FUNCTION IS BEING USED OUTSIDE OF A SIMULA- |
 TION                                                                   |
  BLOCK. IF THE INTEGER VALUE AFFECTS THE VALUE OF THE OBJECTIVE  FUNC- |
 TION,                                                                  |
  THEN AN ERROR WILL PROBABLY OCCUR.                                    |

 In  general, any code that affects the value of the prediction F (with |
 $PRED) or Y (with $ERROR), or their eta and eps partials, affects  the |
 value  of the objective function.  Such code must be continuous, e.g., |
 must not use functions such as INT or MOD, and must not involve condi- |
 tional statements that introduce discontinuities.  The following exam- |
 ples use Model Event Time parameters (MTIME) to avoid  discontinuities |
 in differential equations:                                             |

 Model Time examples                                                    |
 Examples Using MTIME to Model Periodic Discontinuities in $DES         |
 Enterhepatic circulation examples                                      |

 (See mtime, model time examples).                                      |
 (See Circadian Example: Examples Using MTIME to Model Periodic Discon- |
 tinuities in $DES)                                                     |
 (See Enterhepatic circulation examples).

REFERENCES: Guide I Section C.3.5.1
REFERENCES: Guide V Section 5.5


  
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