Use of Bayesian Inference in Crystallographic Structure Refinement via Full Diffraction Profile Analysis.
Sci Rep
; 6: 31625, 2016 08 23.
Article
em En
| MEDLINE
| ID: mdl-27550221
ABSTRACT
A Bayesian inference method for refining crystallographic structures is presented. The distribution of model parameters is stochastically sampled using Markov chain Monte Carlo. Posterior probability distributions are constructed for all model parameters to properly quantify uncertainty by appropriately modeling the heteroskedasticity and correlation of the error structure. The proposed method is demonstrated by analyzing a National Institute of Standards and Technology silicon standard reference material. The results obtained by Bayesian inference are compared with those determined by Rietveld refinement. Posterior probability distributions of model parameters provide both estimates and uncertainties. The new method better estimates the true uncertainties in the model as compared to the Rietveld method.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Estados Unidos