MATLAB: Generate 2-dimensional normal-distribution

covariance-matrixhomeworkMATLABnormal distribution

I want to generate 36 observations from a 2-dimensional normal distribution using the covariance matrix

C = [1 0.8;0.8 1];

Anyone know how to do this?

Best Answer

observations=randn(36,2)*sqrtm(C);

or,

observations=mvnrnd(zeros(36,2),C);

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MATLAB: Covariance terms using fitdist()

pd.ParameterCovariance(2,2) is the covariance of the variance of the estimated normal distribution.

See https://www.mathworks.com/help/stats/prob.normaldistribution.html:

Covariance matrix of the parameter estimates, specified as a p-by-p matrix, where p is the number of parameters in the distribution. The (i,j) element is the covariance between the estimates of the ith parameter and the jth parameter. The (i,i) element is the estimated variance of the ith parameter.

MATLAB: 2-Dimensional Neural network input

 input = [input1; input2];
 target = [ target1; target2 ];

MATLAB equations are, typically, MATrix equations and relatively invariant with respect to dimensionality.

Hope this helps.

Thank you for formally accepting my answer

Greg

Best Answer

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MATLAB: Covariance terms using fitdist()

MATLAB: 2-Dimensional Neural network input

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