Calibration of Sobol indices estimates in case of noisy output

04/02/2018
by   Pavel Prikhodko, et al.
0

This paper presents a simple noise correction method for Sobol' indices estimation. Sobol' indices, especially total Sobol' indices are quite sensitive to the noise in the output and tend to be severly biased (overestimated) if no noise correction is done, which may make their computation meaningless in case of even quite moderate noise levels. Proposed method allows to get approximately unbiased noise free estimation of Sobol' indices at the cost of variance of estimate increase if noise can be represented as a combination of additive and multiplicative stationary noise. impossible to do precise noise correction for more complex noise settings. Proposed method is more straightforward than schemes found in the literature and does not introduce any assumptions on the function and noise distribution (except that it assumes noise to be stationary and be a combination of additive and multiplicative). One of the appealing features is that there is actual analytical noise correction expression derived.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/13/2021

Is Perfect Filtering Enough Leading to Perfect Phase Correction for dMRI data?

Being complex-valued and low in signal-to-noise ratios, magnitude-based ...
research
01/12/2018

Sensitivity indices for independent groups of variables

In this paper, we study sensitivity indices in an additive model and for...
research
10/31/2019

Multiplicative noise in Bayesian inverse problems: Well-posedness and consistency of MAP estimators

Multiplicative noise arises in inverse problems when, for example, uncer...
research
03/31/2022

Test comparison for Sobol Indices over nested sets of variables

Sensitivity indices are commonly used to quantify the relative influence...
research
02/07/2019

DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling

We propose DoPAMINE, a new neural network based multiplicative noise des...
research
07/06/2020

Comparing representational geometries using the unbiased distance correlation

Representational similarity analysis (RSA) tests models of brain computa...
research
02/14/2023

Estimation of coefficients for periodic autoregressive model with additive noise – a finite-variance case

Periodic autoregressive (PAR) time series is considered as one of the mo...

Please sign up or login with your details

Forgot password? Click here to reset