get_grad_trans: Construct parameter transformation for optimization using...

In AIUQ: Ab Initio Uncertainty Quantification

Construct parameter transformation for optimization using exact gradient

Description

Construct parameter transformation for parameters to be optimized over in AIUQ method of SAM class. See 'References'.

Usage

get_grad_trans(theta, d_input, model_name)

Arguments

theta	parameters to be optimized over
d_input	sequence of lag times
model_name	model name for the fitted model, options from ('BM','OU', 'FBM',OU+FBM','user_defined')

Value

A vector of transformed parameters to be optimized over in AIUQ method of SAM class.

Author(s)

Yue He [aut], Xubo Liu [aut], Mengyang Gu [aut, cre]

References

Gu, M., He, Y., Liu, X., & Luo, Y. (2023). Ab initio uncertainty quantification in scattering analysis of microscopy. arXiv preprint arXiv:2309.02468.

Gu, M., Luo, Y., He, Y., Helgeson, M. E., & Valentine, M. T. (2021). Uncertainty quantification and estimation in differential dynamic microscopy. Physical Review E, 104(3), 034610.

AIUQ documentation built on July 2, 2024, 9:06 a.m.