+--------------------------------------------------------------------+
 |                                                                    |
 |                          BAYES EXAMPLE 6                           |
 |                                                                    |
 +--------------------------------------------------------------------+

 This is example6.ctl from the NONMEM 7 distribution medium.  It, along
 with the data file, can be found in the examples directory.

 ;Model Desc: Receptor Mediated Clearance model with Dynamic Change
 ;            in Receptors
 ;Project Name: nm7examples
 ;Project ID: NO PROJECT DESCRIPTION

 $PROB RUN# example6 (from r2compl)
 $INPUT C SET ID JID TIME DV=CONC DOSE=AMT RATE EVID MDV CMT
 $DATA example6.csv IGNORE=C

 ; The new numerical integration solver is used, although ADVAN=9
 ; is also efficient for this problem.

 $SUBROUTINES ADVAN13 TRANS1 TOL=4
 $MODEL NCOMPARTMENTS=3

 $PK
 MU_1=THETA(1)
 MU_2=THETA(2)
 MU_3=THETA(3)
 MU_4=THETA(4)
 MU_5=THETA(5)
 MU_6=THETA(6)
 MU_7=THETA(7)
 MU_8=THETA(8)
 VC=EXP(MU_1+ETA(1))
 K10=EXP(MU_2+ETA(2))
 K12=EXP(MU_3+ETA(3))
 K21=EXP(MU_4+ETA(4))
 VM=EXP(MU_5+ETA(5))
 KMC=EXP(MU_6+ETA(6))
 K03=EXP(MU_7+ETA(7))
 K30=EXP(MU_8+ETA(8))
 S3=VC
 S1=VC
 KM=KMC*S1
 F3=K03/K30

 $DES
 DADT(1) = -(K10+K12)*A(1) + K21*A(2) - VM*A(1)*A(3)/(A(1)+KM)
 DADT(2) = K12*A(1) - K21*A(2)
 DADT(3) =  -VM*A(1)*A(3)/(A(1)+KM) - K30*A(3) + K03

 $ERROR
 CALLFL=0
 ETYPE=1
 IF(CMT.NE.1) ETYPE=0
 IPRED=F
 Y = F + F*ETYPE*EPS(1) + F*(1.0-ETYPE)*EPS(2)

 $THETA
 ;Initial Thetas
 ( 4.0 )  ;[MU_1]
 ( -2.1 ) ;[MU_2]
 ( 0.7 )  ;[MU_3]
 ( -0.17 );[MU_4]
 ( 2.2 ) ;[MU_5]
 ( 0.14 )  ;[MU_6]
 ( 3.7 )  ;[MU_7]
 ( -0.7) ;[MU_8]

 ;Initial Omegas
 $OMEGA BLOCK(8)
 0.2 ;[p]
 -0.0043  ;[f]
 0.2 ;[p]
 0.0048   ;[f]
 -0.0023  ;[f]
 0.2 ;[p]
 0.0032   ;[f]
 0.0059   ;[f]
 -0.0014  ;[f]
 0.2 ;[p]
 0.0029   ;[f]
 0.0027 ;[f]
 -0.00026 ;[f]
 -0.0032  ;[f]
 0.2 ;[p]
 -0.0025  ;[f]
 0.00097  ;[f]
 0.0024   ;[f]
 0.00197  ;[f]
 -0.0080  ;[f]
 0.2 ;[p]
 0.0031   ;[f]
 -0.00571 ;[f]
 0.0030   ;[f]
 -0.0074  ;[f]
 0.0025   ;[f]
 0.0034   ;[f]
 0.2 ;[p]
 0.00973  ;[f]
 0.00862  ;[f]
 0.0041   ;[f]
 0.0046   ;[f]
 0.00061  ;[f]
 -0.0056  ;[f]
 0.0056   ;[f]
 0.2 ;[p]

 $SIGMA
 0.1 ;[p]
 0.1 ;[p]

 $PRIOR NWPRI
 ; Omega prior
 $OMEGAP BLOCK(8)
 0.2 FIX
 0.0 0.2
 0.0 0.0 0.2
 0.0 0.0 0.0 0.2
 0.0 0.0 0.0 0.0 0.2
 0.0 0.0 0.0 0.0 0.0 0.2
 0.0 0.0 0.0 0.0 0.0 0.0 0.2
 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
 ; degrees of freedom for OMEGA prior
 $OMEGAPD
 (8 FIXED)           ;[dfo]

 ; Starting with a short iterative two stage analysis brings the
 ; results closer so less time needs to be spent during the
 ; burn-in of the BAYES analysis

 $EST METHOD=ITS INTERACTION SIGL=4 NITER=15 PRINT=1
      FILE=example6.ext NOABORT NOPRIOR=1

 $EST METHOD=BAYES INTERACTION NBURN=4000 SIGL=4 NITER=10000
      PRINT=10 CTYPE=3 FILE=example6.txt NOABORT NOPRIOR=0

 ; By default, ISAMPLE_M* are 2.  Since there are many data points
 ; per subject, setting these to 1 is enough, and it reduces the
 ; time of the analysis

      ISAMPLE_M1=1 ISAMPLE_M2=1 ISAMPLE_M3=1 IACCEPT=0.4

 $COV MATRIX=R UNCONDITIONAL

REFERENCES: Guide Introduction_7

  
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