Subsections


relax_disp.r2eff_err_estimate

Image relax_disp Image relax_fit

Synopsis

Estimate R2eff errors by the Jacobian matrix.

Defaults

relax_disp.r2eff_err_estimate(spin_id=None, epsrel=0.0, verbosity=1)

Keyword arguments

spin_id: The spin ID string to restrict value setting to.

epsrel: The parameter to remove linear-dependent columns when J is rank deficient.

verbosity: The higher the value, the greater the verbosity.

Description

This is a new experimental feature from version 3.3.

This will estimate R2eff errors by using the exponential decay Jacobian matrix `J' to compute the covariance matrix of the best-fit parameters.

This can be an huge time saving step, when performing model fitting in R1rho. Errors of R2eff values, are normally estimated by time-consuming Monte-Carlo simulations.

This method is inspired from the GNU Scientific Library (GSL).

The covariance matrix is given by: covar = Qxx = (JˆT.W.J)ˆ-1, where the weight matrix W is constructed by the multiplication of an Identity matrix I and a weight array w. The weight array is 1/errorsˆ2, which then gives W = I.w = I x 1/errorsˆ2.

Qxx is computed by QR decomposition, JˆT.W.J=QR, Qxx=Rˆ-1. QˆT. The columns of $ \mathfrak{R}$ which satisfy: |R_{kk}| epsrel |R_{11}| are considered linearly-dependent and are excluded from the covariance matrix (the corresponding rows and columns of the covariance matrix are set to zero).

The parameter `epsrel' is used to remove linear-dependent columns when J is rank deficient.


The relax user manual (PDF), created 2016-10-28.