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matlabrandomcovariance
Laura
Laura

Reputation: 45

Multivariate Random Number Generation in Matlab

I'm probably being a little dense but I'm not very mathsy and can't seem to understand the covariance element of creating multivariate data.

I'm after two columns of random data (representing two correlated variables).

I think I am right in needing to use the mvnrnd function and I understand that 'mu' must be a column of my mean vectors. As I need 4 distinct classes within my data these are going to be (1, 1) (-1 1) (1 -1) and (-1 -1). I assume I will have to do the function 4x with a different column of mean vectors each time and then combine them to get my full data set.

I don't understand what I should put for SIGMA - Matlab help tells me that it must be 'a d-by-d symmetric positive semi-definite matrix, or a d-by-d-by-n array' i.e. a covariance matrix. I don't understand how I create a covariance matrix for numbers that I am yet to generate.

Any advice would be greatly appreciated!

Upvotes: 3

Views: 2518

Answers (2)

Moonlight Knight
Moonlight Knight

Reputation: 313

I think your aim is to generate the simulated multivariate gaussian distributed data. For example, I use

k = 6; % feature dimension mu = rand(1,k); sigma = 10*eye(k,k);

unit matrix by 10 times is a symmetric positive semi-definite matrix. And the gaussian distribution will be more round than other type of sigma.

then you can use it as the above example of mvnrnd function and see the plot.

Upvotes: 0

fpe
fpe

Reputation: 2750

Assuming that I understood your case properly, I would go this way:

data = [normrnd(0,1,5000,1),normrnd(0,1,5000,1)]; %% your starting data series
MU = mean(data,1);
SIGMA = cov(data);

Now, it should be possible to feed mvnrnd with MU and SIGMA:

r = mvnrnd(MU,SIGMA,5000);
plot(r(:,1),r(:,2),'+') %% in case you wanna plot the results

I hope this helps.

Upvotes: 1

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