curvfit2.sce

source code for curve fitting includes regression mechanism

function []=fit();
printf("\n Enter File : ");
fn=scanf("%s");
fp=mopen(fn,'r');
n=mfscanf(fp,'%d');
 printf("\n Enter Order of Equation:");  
 ord=scanf("%d")

for i=1:n,
x(i)=mfscanf(fp,'%f');
y(i)=mfscanf(fp,'%f');
end
      
mclose(fp);

       
        sigma_y=0; sigma_xy=0;
         A(ord+1,ord+1)=0.0;  
         X(ord+1)=0.0;  
        for i=1:n,
           sigma_y=sigma_y+y(i); 
           sigma_xy=sigma_xy+x(i)*y(i);  
        end
      
         sigma(1)=n;
        for j=2:(2*ord)+1,
            sigma(j)=0;
          for i=1:n,
            sigma(j)=sigma(j)+(x(i)^(j-1));
          end
        end 
        
         for j=1:ord+1,     // B matrix preparation
         B(j)=0;
          for i=1:n
           B(j)=B(j)+y(i)*(x(i)^(j-1));
          end
         end
         
                       
          for i=1:ord+1,  // Equation Matrix  preparation
          for j=1:ord+1,      
             A(i,j)=sigma((i+j-1)); 
          end
          end
                           //   X=Inv(A) * B
            
            X=B'*inv(A);
            
         for i=1:n,        // Preparation of Y values yp
         yp(i)=0;
          for j=1:ord+1,
           yp(i)=yp(i)+(x(i)^(j-1))*X(j);
          end 
         
         end
            
    
    //  We know the a and b values  in A+Bx=Y  where Y=log y ;B=log b ; A=log a
    xtitle("    CURVE -FIT   ","       X-Axis","         Y-Axis");
    xset("color",3);
    
    for i=1:n,
         plot(x(i),y(i),'dg')
    end 
    tot=0;
    for i=1:n
      tot=tot+(y(i)-yp(i))^2;
    end
    tot=tot/n;
    printf("generalisation  error is:");
    disp(tot);
     for i=1:n
      tot=tot+abs(y(i)-yp(i));
    end
    printf("absolute value of error is");
    disp(tot/n);
    
   //scf(1);
       xset("color",2);
    plot(x,yp)
    xtitle("    CURVE -FIT   ","       X-Axis","         Y-Axis");
    
    
    endfunction;