| The DTREE Procedure | 
The wildcatter is impressed with the results of calculating 
 the values of perfect information and perfect control.  After 
 comparing those values with the costs of the sounding test 
 and the cost-controlling procedure, he prefers to spend $ on 
 sounding test, which has a potential improvement of $
 on 
 sounding test, which has a potential improvement of $ . 
 He is informed 
 that the sounding will disclose whether the terrain below has 
 no structure (which is bad), open structure (which is okay), 
 or closed structure (which is really hopeful).  The expert also 
 provides him with the following table, which shows the conditional 
 probabilities.
. 
 He is informed 
 that the sounding will disclose whether the terrain below has 
 no structure (which is bad), open structure (which is okay), 
 or closed structure (which is really hopeful).  The expert also 
 provides him with the following table, which shows the conditional 
 probabilities.  
| Seismic Outcomes | |||
| State | No Structure | Open Structure | Closed Structure | 
| Dry | 0.6 | 0.3 | 0.1 | 
| Wet | 0.3 | 0.4 | 0.3 | 
| Soaking | 0.1 | 0.4 | 0.5 | 
To include this additional information into his basic problem, 
 the wildcatter needs to add two stages to his model: a decision 
 stage to represent the decision whether or not to take the 
 sounding test, and one chance stage to represent the uncertain 
 test result.  The new STAGEIN= 
 data set is
 
  
       /* -- create the STAGEIN= data set              -- */ 
    data Dtoils2; 
       format _STNAME_ $12. _STTYPE_ $2.  _OUTCOM_ $14. 
             _SUCCES_ $12. _REWARD_ dollar12.0; 
       input _STNAME_ & _STTYPE_ & _OUTCOM_ & 
             _SUCCES_ & _REWARD_ dollar12.0; 
       datalines; 
    Drill        D   Drill           Cost                 . 
    .            .   Not_Drill       .                    . 
    Cost         C   Low             Oil_Deposit          . 
    .            .   Fair            Oil_Deposit          . 
    .            .   High            Oil_Deposit          . 
    Oil_Deposit  C   Dry             .                    . 
    .            .   Wet             .                    . 
    .            .   Soaking         .                    . 
    Sounding     D   Noseismic       Drill                . 
    .            .   Seismic         Structure     -$60,000 
    Structure    C   No_Struct       Drill                . 
    .            .   Open_Struct     Drill                . 
    .            .   Closed_Struct   Drill                . 
    ;
 
Note that the cost for the seismic soundings is represented as negative reward (of the outcome Seismic) in this data set. The conditional probabilities for stage Structure are added to the PROBIN= data set as follows:
  
       /* -- create PROBIN= data set                   -- */ 
    data Dtoilp2; 
       format _EVENT1 $10. _EVENT2 $12. _EVENT3 $14. ; 
       input _GIVEN_ $ _EVENT1 $ _PROB1 
             _EVENT2 $ _PROB2  _EVENT3 $ _PROB3; 
       datalines; 
    .       Low       0.2 Fair        0.6 High          0.2 
    .       Dry       0.5 Wet         0.3 Soaking       0.2 
    Dry     No_Struct 0.6 Open_Struct 0.3 Closed_Struct 0.1 
    Wet     No_Struct 0.3 Open_Struct 0.4 Closed_Struct 0.3 
    Soaking No_Struct 0.1 Open_Struct 0.4 Closed_Struct 0.5 
    ;
 
It is not necessary to make any change to the PAYOFFS= data set. To evaluate his new model, the wildcatter invokes PROC DTREE as follows:
  
       /* -- PROC DTREE statements                     -- */ 
    title "Oil Wildcatter's Problem"; 
  
    proc dtree stagein=Dtoils2 
               probin=Dtoilp2 
               payoffs=Dtoilu1 
               nowarning; 
  
       evaluate;
 
As before, the following messages are written to the SAS log:
  
    NOTE: Present order of stages: 
  
          Sounding(D), Structure(C), Drill(D), Cost(C), 
          Oil_Deposit(C), _ENDST_(E). 
  
    NOTE: The currently optimal decision yields 140000.
 
The following SUMMARY statements produce optimal decision summary as shown in Figure 5.5 and Figure 5.6:
  
       summary / target=Sounding; 
       summary / target=Drill;
 
The optimal strategy for the oil-drilling problem is found to be the following:
 .
. - $
 - $ = $
 = $ (this quantity is also called the value of imperfect 
         information or the value of sample information), 
         but it costs $
 
         (this quantity is also called the value of imperfect 
         information or the value of sample information), 
         but it costs $ ; therefore, it should not be taken.
; therefore, it should not be taken. 
 | 
 The DTREE Procedure Optimal Decision Summary 
 
 
 
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Note that the value of sample information also can be obtained by using the following statements:
  
       modify Seismic reward 0; 
       evaluate;
 
The following messages, which appear in the SAS log, show the expected 
 payoff with soundings test is $ .  Recall that the expected 
 value without test information is $
.  Recall that the expected 
 value without test information is $ .  Again, following the 
 previous calculation, the value of test information is 
 $
.  Again, following the 
 previous calculation, the value of test information is 
 $ - $
 - $ = $
 = $ .
.
  
    NOTE: The reward of outcome Seismic has been changed to 0. 
  
    NOTE: The currently optimal decision yields 180100.
 
Now, the wildcatter has the information to make his best decision.
Copyright © 2008 by SAS Institute Inc., Cary, NC, USA. All rights reserved.