Generating random data from Kernel density estimator
9 次查看(过去 30 天)
显示 更早的评论
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.
0 个评论
回答(3 个)
Poulomi Ganguli
2019-10-5
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);
0 个评论
Abraham
2018-9-24
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
0 个评论
hamid mirzaeefard
2019-10-5
Hi.
This is my question too.
I need random data with kernel distribution but I don't know how can do it.
0 个评论
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!