Thank you @xztt.
I’m recalling I’ve been reading a bit about Sobol and Morris methods some time ago, however, I’m usually missing the drawings [seriously in most of those books I am reading I usually always missing the notation :- )]. It was some time ago thus I’m just wondering, are Sobol and Morris methods in the same brackets as singular vectors, Kalman filter (derivatives), bred-vectors or i.e. empirical orthogonal function or are these terms closer to the Koopman operator?
So from what you have said above I don’t know if this will concern you as GSA is concerned with seeing how the inputs affect the outputs. i.e the input parameters of your dynamical system.
Yeah, I’m wondering about similar thing.
However another package to see the uncertainty in the outputs is Uncertainty Quantification · DifferentialEquations.jl
But how can I do it with this package?
What I managed to do so far is:
a) to visualize this uncertainty in a form of some strings on a lattice (which allows me to (usually) notice some clusters by my bare eye [however, I still don’t quite fully know how to computationally cluster those string in a spatial context (for this I was hoping to ping @juliohm in the near future with a hope of some advice) and also I have to admit that I still hope to mark some readings on those strings that would indicate the properties of the dynamical systems between which my particle is moving so I could better understand it but still with so many ensemble members it’s not that easy],
b) to visualize decomposition of those ensembles, particularly to visualize in a spatial and time context relationships between the deterministic prediction and each perturbed member of the ensemble but not only this,
d) to visualize in a spatial and time context relationship between updated (new, the most up to date, near real time data) with each perturbed ensemble member so I could maybe get some indication about the next deterministic prediction run.
Would you maybe have any additional suggestions?
I am currently writing up a paper now so would be good to include a paper such as this
Wow, it sounds super interesting, is there maybe any chance to take a look at a draft of your piece?