Examples
// 2 independent random variables // (Gaussian law, mean = 0, stdev = 1) samples = grand(2,1000,"nor", 0, 1); [meanv,covm] = CL_stat(samples) [cor,sd] = CL_cov2cor(covm) |  |  |
Statistics on samples
[meanv,covm] = CL_stat(samples)
Computes the mean value and the covariance matrix of samples.
Set of drawn vectors. Each vector (= column vector) is made of P indidual variables. The number of samples (N) is the number of columns. (PxN)
Estimated mean value (Px1)
Estimated covariance matrix (PxP)
CNES - DCT/SB
// 2 independent random variables // (Gaussian law, mean = 0, stdev = 1) samples = grand(2,1000,"nor", 0, 1); [meanv,covm] = CL_stat(samples) [cor,sd] = CL_cov2cor(covm) | | |