# Difference between rng('shuffle') and NO rng for estimating with MLE

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Mustafa Vural 2020 年 6 月 20 日
コメント済み: Rik 2020 年 12 月 7 日
I am trying to estimate a 3-parameter weibul distribution with random numbers. But I dont understand the difference between rng('shuffle') and NO rng('shuffle'), I mean deleting the line. Both lines estimates random numbers in my code. Can someone tell me the difference?
And if you can give me any advice for my code for estimating a 3-parameter weibul estimation, I would appreciate that.
clear all
n = 1000;
t0 = 0.5;
b_A = 1:5;
T_A = 1:5;
LowerBound= [0 0 0];
rng('shuffle');
data = zeros(n,length(b_A),length(T_A));
params = zeros(length(b_A),length(T_A));
data2P = zeros(n,length(b_A),length(T_A));
params2p = zeros(length(b_A),4,length(T_A));
for k= T_A
for i= b_A
data(:,i,k) = wblrnd(i,k, [n,1]) + t0;
data2P(:,i,k) = wblrnd(b_A(i),T_A(k), [n,1]);
start = [i k t0];
custompdf = @(x,a,b,c) (x>c).*(b/a).*(((x-c)/a).^(b-1)).*exp(-((x-c)/a).^b);
opt = statset('MaxIter',1e5,'MaxFunEvals',1e5,'FunValCheck','off');
params(i,1:3,k) = mle(data(:,i,k),'pdf',custompdf,'start',start,'Options',opt,'LowerBound',LowerBound,'UpperBound',[Inf Inf min(data(:,i,k))])
params(i,4,k) = i;
params(i,5,k) = k;
params(i,6,k) = t0;
params2p(i,1:2,k) = wblfit(data2P(:,i,k));
params2p(i,3,k) = i;
params2p(i,4,k) = k;
end
end
##### 1 件のコメント表示非表示 なし
Rik 2020 年 12 月 7 日
Please do not delete your question. If you feel this is a beginner question: there are many beginners, so be nice to them. They might come across your question and learn from it.
I made a capture so people can revert your edit if you attempt to vandalize your question.

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### 採用された回答

the cyclist 2020 年 6 月 21 日
If you start a fresh instance of MATLAB, and generate a sequence of pseudorandom numbers, it will always be the same sequence. (Try it!)
If you do not use the
rng('shuffle')
then you will get the numbers from that sequence. If you do use it, then instead of traveling along that predetermined sequence of numbers, you will leap to a different point on that sequence, based on the time when you make the call to the function.
##### 8 件のコメント表示非表示 7 件の古いコメント
Walter Roberson 2020 年 6 月 21 日

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