I’m curious: is it making fixed standard assumptions about those annoying ergodic Gaussian questions, or is it clever enough to figure out the answers for itself?
The documentation says it’s using the Levenberg-Marquardt algorithm, which, as far as I can understand, doesn’t make any assumptions about the data, but only converges towards local minima for the least-squares distance between dataset and the output of the function.
(I don’t think this will matter much for me in practice, though).
I’m curious: is it making fixed standard assumptions about those annoying ergodic Gaussian questions, or is it clever enough to figure out the answers for itself?
The documentation says it’s using the Levenberg-Marquardt algorithm, which, as far as I can understand, doesn’t make any assumptions about the data, but only converges towards local minima for the least-squares distance between dataset and the output of the function.
(I don’t think this will matter much for me in practice, though).