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Generating random data from Kernel density estimator

22 Ansichten (letzte 30 Tage)
Pg
Pg am 5 Nov. 2011
Beantwortet: Poulomi Ganguli am 5 Okt. 2019
Hi,
I h've fitted my data to kernel PDF. Now to get random number from this distribution I want to generate using Metropolis-Hastings algorithm. After lot of search I found that mhsample is a built in function in MATLAB. but unable to understand how to use it for my problem. I h've problem in defining propdf and proprnd argument. If anybody can help me a bit, will be helpful.

Antworten (3)

Poulomi Ganguli
Poulomi Ganguli am 5 Okt. 2019
This is simple. First, estimate kernel density parameters from data vector, using fitdist:
pd = fitdist(X,'kernel');
Use this parameters to generate random samples, where 100x1 is the desired random samples:
Y = random(pd, [100,1]);
or Y = pd.random(100,1);

Abraham
Abraham am 24 Sep. 2018
Hello, I would like to ask the same question because in the information provided by the matlab help it seems that the "Metropolis-Hastings" only sampling from analytical expressions.
Cheers

hamid mirzaeefard
hamid mirzaeefard am 5 Okt. 2019
Hi.
This is my question too.
I need random data with kernel distribution but I don't know how can do it.

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