Tugas 2 : Macam-macam Fungsi Distribusi

1. DISTRIBUSI EKSPONSIAL (lamda)

Function Eksponensial (beta : double) : double;

Var u : double;

Begin

   u := random;

   Eksponensial := -beta * ln(u);

End;

2. DISTRIBUSI UNIFORM (a,b)

Function Uniform (a,b : double) : double;

Var u : double;

Begin

  u:= random;

   Uniform := (b-a) * u + a;

End;

3. DISTRIBUSI NORMAL  (µ, sigma)

Procedure Normal (mean,variance : double ; Var z1,z2 : double);

Var u1,u2,v1,v2,w,y,x1,x2 : double;

Begin

   Repeat

      u1 := random;

      u2 := random;

      v1 := 2 * u1 - 1;

      v2 := 2 * u2 - 1;

      w := sqr(v1) + sqr(v2);

      if w <= 1 then

         begin

            y := sqrt ((-2*ln(w))/w);

            x1 := v1 * y;

            x2 := v2 * y;

            z1 := sqrt (variance) * x1 + mean;

            z2 := sqrt (variance) * x2 + mean;

         end

   Until w <= 1;

End;

4. DISTRIBUSI LOGNORMAL

procedure lognormal (mean,varr : double;

Var  zln1,zln2 : double);

Var y1, y2 : double;

begin

    Normal (mean,varr,y1,y2);

    zln1 := exp(y1);

    zln2 := exp(y2);

end;

5. DISTRIBUSI T-STUDENT

function tdistribution(m:integer):double;

{ created :

         based on Principles of Random Variate Generation

                   by John Dagpunar, 1988

         published by Claredon Press - OXFORD

   please check if any other theory of t-distribution }

Label r2;

Var v,x,r,s,c,a,f,g,mm : real;

begin

  mm:=0;

  if m < 1 then

  begin

     writeln('impermissible degrees of freedom.');

     halt;

  end;

  if (m <> mm) then

  begin

     s:=m;

     c:=-0.25*(s+1);

     a:=4/power((1+1/s),c);

     f:=16/a;

     if m>1 then

     begin

       g:=s-1;

       g:=power(((s+1)/g),c)*sqrt((s+s)/g);

     end else

            g := 1;

     mm:=m;

  end;

r2:repeat

    r:=random;

  until r > 0.0;

  x:=(2*random-1)*g/r;

  v:=x*x;

  if (v>(5-a*r)) then

  begin

     if ((m>=3) and (r*(v+3)>f)) then goto r2;

     if (r>power((1+v/s),c)) then goto r2;

  end;

  tdistribution :=x;

end;

begin

   tipe11[1]:=0.2;

   tipe11[1]:=0.3;

   tipe11[1]:=0.5;

   tipe11[1]:=0.8;

   tipe11[1]:=1.0;

end.

6. DISTRIBUSI WEIBULL

Function Weibull (alfa,beta: double) : double;

Var u,z : double;

Begin

   u := random;

   z := -ln(v);

   Weibull := beta * exp (ln(z)/alfa);

End;