*************************************;
*** begin scoring code for regression;
*************************************;

length _WARN_ $4;
label _WARN_ = 'Warnings' ;

length I_BAD $ 12;
label I_BAD = 'Into: BAD' ;
*** Target Values;
array RGDRF [2] $12 _temporary_ ('1' '0' );
label U_BAD = 'Unnormalized Into: BAD' ;
*** Unnormalized target values;
ARRAY RGDRU[2]  _TEMPORARY_ (1 0);

*** Generate dummy variables for BAD ;
drop _Y ;
label F_BAD = 'From: BAD' ;
length F_BAD $ 12;
F_BAD = put( BAD , BEST12. );
%DMNORMIP( F_BAD )
if missing( BAD ) then do;
   _Y = .;
end;
else do;
   if F_BAD = '0'  then do;
      _Y = 1;
   end;
   else if F_BAD = '1'  then do;
      _Y = 0;
   end;
   else do;
      _Y = .;
   end;
end;

drop _DM_BAD;
_DM_BAD=0;

*** Check CLAG_K4W for missing values ;
if missing( CLAG_K4W ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Check DEBTINC for missing values ;
if missing( DEBTINC ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Check INDELINQ for missing values ;
if missing( INDELINQ ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Check INDEROG for missing values ;
if missing( INDEROG ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Check LOAN_9QB for missing values ;
if missing( LOAN_9QB ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Check MORT_G0S for missing values ;
if missing( MORT_G0S ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Check YOJ_34KW for missing values ;
if missing( YOJ_34KW ) then do;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;

*** Generate dummy variables for JOB ;
drop _2_0 _2_1 _2_2 _2_3 _2_4 ;
*** encoding is sparse, initialize to zero;
_2_0 = 0;
_2_1 = 0;
_2_2 = 0;
_2_3 = 0;
_2_4 = 0;
if missing( JOB ) then do;
   _2_0 = .;
   _2_1 = .;
   _2_2 = .;
   _2_3 = .;
   _2_4 = .;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;
else do;
   length _dm7 $ 7; drop _dm7 ;
   %DMNORMCP( JOB , _dm7 )
   _dm_find = 0; drop _dm_find;
   if _dm7 <= 'OTHER'  then do;
      if _dm7 <= 'OFFICE'  then do;
         if _dm7 = 'MGR'  then do;
            _2_0 = 1;
            _dm_find = 1;
         end;
         else do;
            if _dm7 = 'OFFICE'  then do;
               _2_1 = 1;
               _dm_find = 1;
            end;
         end;
      end;
      else do;
         if _dm7 = 'OTHER'  then do;
            _2_2 = 1;
            _dm_find = 1;
         end;
      end;
   end;
   else do;
      if _dm7 <= 'SALES'  then do;
         if _dm7 = 'PROFEXE'  then do;
            _2_3 = 1;
            _dm_find = 1;
         end;
         else do;
            if _dm7 = 'SALES'  then do;
               _2_4 = 1;
               _dm_find = 1;
            end;
         end;
      end;
      else do;
         if _dm7 = 'SELF'  then do;
            _2_0 = -1;
            _2_1 = -1;
            _2_2 = -1;
            _2_3 = -1;
            _2_4 = -1;
            _dm_find = 1;
         end;
      end;
   end;
   if not _dm_find then do;
      _2_0 = .;
      _2_1 = .;
      _2_2 = .;
      _2_3 = .;
      _2_4 = .;
      substr(_warn_,2,1) = 'U';
      _DM_BAD = 1;
   end;
end;

*** Generate dummy variables for NINQ_76F ;
drop _3_0 _3_1 ;
if missing( NINQ_76F ) then do;
   _3_0 = .;
   _3_1 = .;
   substr(_warn_,1,1) = 'M';
   _DM_BAD = 1;
end;
else do;
   length _dm17 $ 17; drop _dm17 ;
   _dm17 = put( NINQ_76F , NINQ_T5_17. );
   %DMNORMIP( _dm17 )
   if _dm17 = '0001:LOW-0.5'  then do;
      _3_0 = 1;
      _3_1 = 0;
   end;
   else if _dm17 = '0003:1.5-HIGH'  then do;
      _3_0 = -1;
      _3_1 = -1;
   end;
   else if _dm17 = '0002:0.5-1.5'  then do;
      _3_0 = 0;
      _3_1 = 1;
   end;
   else do;
      _3_0 = .;
      _3_1 = .;
      substr(_warn_,2,1) = 'U';
      _DM_BAD = 1;
   end;
end;

*** If missing inputs, use averages;
if _DM_BAD > 0 then do;
   _P0 = 0.2023079697;
   _P1 = 0.7976920303;
   goto RGDR1;
end;

*** Compute Linear Predictor;
drop _TEMP;
drop _LP0;
_LP0 = 0;

***  Effect: CLAG_K4W ;
_TEMP = CLAG_K4W ;
_LP0 = _LP0 + (   -0.78690764730093 * _TEMP);

***  Effect: DEBTINC ;
_TEMP = DEBTINC ;
_LP0 = _LP0 + (    0.06939430135677 * _TEMP);

***  Effect: INDELINQ ;
_TEMP = INDELINQ ;
_LP0 = _LP0 + (    1.60218107435311 * _TEMP);

***  Effect: INDEROG ;
_TEMP = INDEROG ;
_LP0 = _LP0 + (    1.36551647764982 * _TEMP);

***  Effect: JOB ;
_TEMP = 1;
_LP0 = _LP0 + (    0.02339994301053) * _TEMP * _2_0;
_LP0 = _LP0 + (   -0.57526212520046) * _TEMP * _2_1;
_LP0 = _LP0 + (    -0.0385300730656) * _TEMP * _2_2;
_LP0 = _LP0 + (    0.00059411038964) * _TEMP * _2_3;
_LP0 = _LP0 + (    0.49313841586884) * _TEMP * _2_4;

***  Effect: LOAN_9QB ;
_TEMP = LOAN_9QB ;
_LP0 = _LP0 + (    -0.5320614549918 * _TEMP);

***  Effect: MORT_G0S ;
_TEMP = MORT_G0S ;
_LP0 = _LP0 + (   -0.34740449441048 * _TEMP);

***  Effect: NINQ_76F ;
_TEMP = 1;
_LP0 = _LP0 + (   -0.21792456211849) * _TEMP * _3_0;
_LP0 = _LP0 + (   -0.17253416894202) * _TEMP * _3_1;

***  Effect: YOJ_34KW ;
_TEMP = YOJ_34KW ;
_LP0 = _LP0 + (   -0.27770947608238 * _TEMP);

*** Naive Posterior Probabilities;
drop _MAXP _IY _P0 _P1;
_TEMP =     9.15445900940893 + _LP0;
if (_TEMP < 0) then do;
   _TEMP = exp(_TEMP);
   _P0 = _TEMP / (1 + _TEMP);
end;
else _P0 = 1 / (1 + exp(-_TEMP));
_P1 = 1.0 - _P0;

RGDR1:

*** Residuals;
if (_Y = .) then do;
   R_BAD1 = .;
   R_BAD0 = .;
end;
else do;
    label R_BAD1 = 'Residual: BAD=1' ;
    label R_BAD0 = 'Residual: BAD=0' ;
   R_BAD1 = - _P0;
   R_BAD0 = - _P1;
   select( _Y );
      when (0)  R_BAD1 = R_BAD1 + 1;
      when (1)  R_BAD0 = R_BAD0 + 1;
   end;
end;


*** Update Posterior Probabilities;

*** Decision Processing;
label D_BAD_ = 'Decision: BAD' ;
label EP_BAD_ = 'Expected Profit: BAD' ;
label BP_BAD_ = 'Best Profit: BAD' ;
label CP_BAD_ = 'Computed Profit: BAD' ;

length D_BAD_ $ 5;

D_BAD_ = ' ';
EP_BAD_ = .;
BP_BAD_ = .;
CP_BAD_ = .;

*** Compute Expected Consequences and Choose Decision;
_decnum = 1; drop _decnum;

D_BAD_ = '1' ;
EP_BAD_ = _P0 * 1 + _P1 * 0;

*** Decision Matrix;
array RGdema [2,1] _temporary_ (
/* row 1 */  1
/* row 2 */  0
);

*** Find Index of Target Category;
drop _tarnum; select( F_BAD );
   when('1' ) _tarnum = 1;
   when('0' ) _tarnum = 2;
   otherwise _tarnum = 0;
end;
if _tarnum <= 0 then goto RGdeex;

*** Computed Consequence of Chosen Decision;
CP_BAD_ = RGdema [_tarnum,_decnum];

*** Best Possible Consequence of Any Decision without Cost;
array RGdebe [2] _temporary_ ( 1 0);
BP_BAD_ = RGdebe [_tarnum];


RGdeex:;

*** End Decision Processing ;

*** Posterior Probabilities and Predicted Level;
label P_BAD1 = 'Predicted: BAD=1' ;
label P_BAD0 = 'Predicted: BAD=0' ;
P_BAD1 = _P0;
_MAXP = _P0;
_IY = 1;
P_BAD0 = _P1;
if (_P1 - _MAXP > 1e-8) then do;
   _MAXP = _P1;
   _IY = 2;
end;
I_BAD = RGDRF[_IY];
U_BAD = RGDRU[_IY];

*************************************;
***** end scoring code for regression;
*************************************;