I'm currently working on dynamic system identification and performing Monte Carlo runs with different noise realisations at a given $SNR$ ratio. Once the parameters converge, I save them in a matrix which contains all the converged parameters for the runs. My question is really basic (maybe even dumb). If I'm willing to provide the mean and standard deviation of each parameter, is the classic formula $\sigma = \sqrt{\frac{1}{N-1}\sum_{k=1}^N(x_i -\bar{x})^2}$ still correct, or do I need to take into account the whole number of estimated parameters and use another expression ?
2026-03-28 08:28:08.1774686488
Standard deviation on Monte Carlo runs
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