A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is
Development of a Monte Carlo—Library Least-Squares code package for the EDXRF inverse problem
The Monte Carlo -Library Least-Squares (MCLLS) approach has now been developed, implemented, and tested for solving the inverse problem of EDXRF sample analysis. It consists of a linear library least-squares (LLS) code and a comprehensive Monte Carlo code named CEARXRF that is capable of calculating the unknown sample spectrum, all the elemental library spectra in the sample, and the differential operators for each library spectrum with respect to each element. Two codes with Graphical Userdoi:10.1154/1.1913722 fatcat:c2g427uhofguppfom2gydd3lly