get_morris_sensitivity_indices

pyapprox.sensitivity_analysis.get_morris_sensitivity_indices(elem_effects)

Compute the Morris sensitivity indices mu and sigma from the elementary effects computed for a set of trajectories.

Mu is the mu^star from Campolongo et al.

Parameters

elem_effectsnp.ndarray(nvars,ntrajectories,nqoi)

The elementary effects of each variable for each trajectory and quantity of interest (QoI)

Returns

munp.ndarray(nvars,nqoi)

The sensitivity of each output to each input. Larger mu corresponds to higher sensitivity

sigma: np.ndarray(nvars,nqoi)

A measure of the non-linearity and/or interaction effects of each input for each output. Low values suggest a linear realationship between the input and output. Larger values suggest a that the output is nonlinearly dependent on the input and/or the input interacts with other inputs