@N
Size: a a a
@N
PO
FO
RO
RO
PO
@N
RO
PO
FO
PO
PO
RO
RO
RO
@N
RO
PO
mean = np.mean(distrs[i],axis=0)
means[i] = mean
covariance = 1 / tau * np.identity(len(mean))
covariance += np.mean(np.array([np.outer(x, x) for x in distrs[i]]),axis=0) - np.outer(mean, mean)
std = np.sqrt(covariance.diagonal())
stds[i] = std
RO
RO