%0 Journal Article %1 David2001 %A David, W. I. F. %A Sivia, D. S. %D 2001 %J J. Appl. Cryst. %K *file-import-13-09-19 background-estimation bayesian-analysis cpsst %N 3 %P 318--324 %R 10.1107/s0021889801004332 %T Background estimation using a robust Bayesian analysis %U http://dx.doi.org/10.1107/s0021889801004332 %V 34 %X A novel method for the estimation of the background in a powder diffraction pattern has been developed using a robust Bayesian analysis. In formulating a probabilistic approach to background fitting, the diffraction peaks are considered to be nuisance data that must be taken into account. The underlying probability theory is discussed in terms of going beyond the Gaussian approximation normally associated with counting statistics and least-squares analysis. Various examples are presented that illustrate the general applicability of this approach.

@article{David2001, abstract = {{A novel method for the estimation of the background in a powder diffraction pattern has been developed using a robust Bayesian analysis. In formulating a probabilistic approach to background fitting, the diffraction peaks are considered to be nuisance data that must be taken into account. The underlying probability theory is discussed in terms of going beyond the Gaussian approximation normally associated with counting statistics and least-squares analysis. Various examples are presented that illustrate the general applicability of this approach.}}, added-at = {2019-03-11T21:00:05.000+0100}, author = {David, W. I. F. and Sivia, D. S.}, biburl = {https://www.bibsonomy.org/bibtex/28165a66d3963acbe5be495dc8d09c80b/fairybasslet}, citeulike-article-id = {10845448}, citeulike-linkout-0 = {http://dx.doi.org/10.1107/s0021889801004332}, citeulike-linkout-1 = {http://scripts.iucr.org/cgi-bin/paper?S0021889801004332}, doi = {10.1107/s0021889801004332}, interhash = {0a8165af96583b2b23d06ecdbc46d540}, intrahash = {8165a66d3963acbe5be495dc8d09c80b}, journal = {J. Appl. Cryst.}, keywords = {*file-import-13-09-19 background-estimation bayesian-analysis cpsst}, month = jun, number = 3, pages = {318--324}, posted-at = {2012-07-01 13:09:16}, priority = {2}, timestamp = {2019-03-11T21:06:37.000+0100}, title = {{Background estimation using a robust Bayesian analysis}}, url = {http://dx.doi.org/10.1107/s0021889801004332}, volume = 34, year = 2001 }