The modeling error refers to errors caused by using for example an imperfect forward model, see [HCM14].

A Gaussian model of the modeling error can be specified by the mean, dt, and the covariance, Ct.

For example

data{1}.dt=[0 0 0];
data{1}.Ct=[4 4 4; 4 4 4; 4 4 4];

is equivalent to

data{1}.Ct=4

which implies a zero mean modeling error with a covariance model where all model parameters has a covariance of 4.

sippi_compute_modelization_forward_error can be used to estimate the modeling error related to using an approximate forward model. See the tomography example, for an example of accounting for correlated modeling errors, following [HCM14].