Difference between revisions of "Maximum likelihood"
From Online Dictionary of Crystallography
BrianMcMahon (talk | contribs) |
BrianMcMahon (talk | contribs) m (Tidied translations.) |
||
(2 intermediate revisions by 2 users not shown) | |||
Line 1: | Line 1: | ||
+ | <font color="blue">Maximum de vraisemblance</font> (''Fr''). <font color="red">Maximale Wahrscheinlichkeit</font> (''Ge''). <font color="black">Metodo della massima verosimiglianza</font> (''It''). <font color="purple">最尤法</font> (''Ja''). <font color="green">Máxima verosimilitud</font> (''Sp''). | ||
+ | |||
+ | |||
An approach to structure [[refinement]] in which the parameters of a structural model are modified to optimize the statistical probability of generating a set of observed intensities. The technique is often used in the refinement of structures of biological macromolecules, where the unfavourable parameter-to-observation ratio often leads to overfitted data and consequent systematic errors in least-squares minimization procedures. | An approach to structure [[refinement]] in which the parameters of a structural model are modified to optimize the statistical probability of generating a set of observed intensities. The technique is often used in the refinement of structures of biological macromolecules, where the unfavourable parameter-to-observation ratio often leads to overfitted data and consequent systematic errors in least-squares minimization procedures. | ||
[[Category:Biological crystallography]] | [[Category:Biological crystallography]] | ||
[[Category:Structure determination]] | [[Category:Structure determination]] |
Latest revision as of 12:40, 16 November 2017
Maximum de vraisemblance (Fr). Maximale Wahrscheinlichkeit (Ge). Metodo della massima verosimiglianza (It). 最尤法 (Ja). Máxima verosimilitud (Sp).
An approach to structure refinement in which the parameters of a structural model are modified to optimize the statistical probability of generating a set of observed intensities. The technique is often used in the refinement of structures of biological macromolecules, where the unfavourable parameter-to-observation ratio often leads to overfitted data and consequent systematic errors in least-squares minimization procedures.