SIMULASI

Jumat, 02 Oktober 2009

Keacakan Data

Algoritma dalam pembuatan PiQi Plot adalah sebagai berikut :
1. Memulai perintah pemrograman.
2. Mengurutkan data bangkitan
3. Menentukan nilai Pi.
4. Menentukan nilai Qi
5. Membuat scatterplot antara nilai Qi dengan X(1).
6. Perintah pemrograman selesai.

Rabu, 16 September 2009

Minal Aidzin Wal Faidzin

MTV bilang kalo mo minta maap g ush nunggu lebaran.
Org bijak blg kerennya kalo mnt maap duluanUst.
Jefri blg org cakep mnt maap gk prl disuruh.
Kyai blg org jujur ga perlu malu utk minta maap.
Jd krn mrs anak nongkrong yg jujur, keren cakep dan baekya gw ngucapin minal aidzin wal faizin , mohon maaf lahir dan batin ..

Met Lebaran all

Faith makes all things possible.
Hope makes all things work.
Love makes all things beautiful.
May you have all of the three.
Happy Iedul Fitri.”

Sabtu, 12 September 2009

Pengantar

Assalammualaikum Wr Wb
Nama : Karlinarachmasita
Nrp : 1307 100 042

Kali ini membahas mengenai pembangkitan bilangan acak pseudo-random generation. Silahkan dilihat hasil postingan saya.

Wassalam;

Tugas Buat function dari masing-masing distribusi

1. Uniform (a,b)
Fungsi Distribusi Uniform
Function Uniform (a,b : double) : double;
Var u : double;
Begin
u := random;
Uniform := (b-a) * u + a;
End;

2. eksponential
Function Eksponensial (beta : double) : double;
Var u : double;
Begin
u := random;
Eksponensial := -beta * ln(u);
End;

3. normal
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. 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. weibul
Function Weibull (alfa,beta: double) : double;
Var u,z : double;
Begin
u := random;
z := -ln(u);
Weibull := beta * exp (ln(z)/alfa);
End;

6. t-student
function tdistribution(m:integer):double;

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;