How to use mvnrnd function ?
I need to generate a matrix whose elements follow normal distribution with zero mean and Q covariance matrix . I know Q (some positive definite matrix)
I'm using the following code
Q size is (4,4) MU=zeros(1,4); noise=mvnrnd(MU,Q,10)+1j*mvnrnd(MU,Q,10);
MY noise size should be (4,10) but i m getting size as (10,4)
Thanks

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Alka Nair
Alka Nair el 10 de Abr. de 2015

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The documentation of MVNRND suggests that the syntax is
>> r = mvnrnd(MU,SIGMA,cases) and r = mvnrnd(MU,SIGMA,cases) returns a cases-by-d matrix R of random vectors chosen from the multivariate normal distribution with a common 1-by-d mean vector MU, and a common d-by-d covariance matrix SIGMA. As cases is 10 in your case and d is 4, you are observing the dimension 10*4 for 'noise'.
Please refer to the documentation at:

3 comentarios

Betha Shirisha
Betha Shirisha el 10 de Abr. de 2015
@ Alka Nair thanks..:)
But if r is of size (cases,d),then it's covariance matrix will be of size (cases,cases)..then sigma should also be of size (cases,cases),right ?
John D'Errico
John D'Errico el 10 de Abr. de 2015
Editada: John D'Errico el 10 de Abr. de 2015
No, no no.
cases, the third argument is the NUMBER of samples to be generated. Those samples are independent of each other.
The covariance matrix is the covariance of those random variables, but not from sample to sample. Again, the samples are INDEPENDENT.
So if the random variable lives in a d-dimensional space, then you will need to pass in a vector of length d for mu, and a matrix of size dxd for sigma. Then expect that the result will be of size (cases,d).
Betha Shirisha
Betha Shirisha el 10 de Abr. de 2015
@ john thanks..

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