Morris Vs Sobol Method Global Sensitivity analysis

[ChrisRackauckas]

@j_u

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?

Not close.

@j_u

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?

This is not related to this thread at all, you may want to start a new one.

@xztt

Will be very interested in that paper I assume there will be some comparisons to the standard SAlib and the countless toolboxes that exist in Matlab I can only postulate what the differences will be .

You’ll surely be disappointed. We’re just doing a JOSS submission because there’s nothing particularly special about the package, no new methods or anything, it’s just a well-tested, fast, and easy to parallelize version of the methods.

[PRE REVIEW]: GlobalSensitivity.jl: julia package for performant global sensitivity analysis

Comparisons don’t make sense for the GSA package because all of the time is spent in the f evaluations, so of course we’d beat SALib and MATLAB, but that benchmark would just be a benchmark of the ODE solvers and parallelism overhead in any realistic example. So yes, it will be like 100x-1000x faster for cases people use it for, but the reason wouldn’t be GlobalSensitivity.jl per say, rather the f is faster because it’s using some other SciML package (or it’s using the batching interface to implement parallelism, something that is quite unique but is just a “this is the right way to implement it” kind of thing)