modify your search
 Results for DC.creator="E." AND DC.creator="Prince"   page 2 of 3 pages.
Stereochemical constraints as observational equations
Prince, E., Finger, L. W. and Konnert, J. H.  International Tables for Crystallography (2006). Vol. C, Section 8.3.2.1, pp. 698-701 [ doi:10.1107/97809553602060000611 ]
... 3.65937 O1 -0.48899 -2.49684 3.46331 N2 -0.00450 -0.81846 4.87646 Glu E C[beta] -0.06551 -0.87677 1.25157 C[gamma] 1.15947 -1.71468 1.59818 ... 13.01-13.26. Bangalore: Indian Academy of Sciences. Hestenes, M. & Stiefel, E. (1952). Methods of conjugate gradients for solving linear systems. ... Cryst. A34, 578-582. Schomaker, V., Waser, J., Marsh, R. E. & Bergman, G. (1959). To fit a plane or ...
     [more results from section 8.3.2 in volume C]

Direct application of constraints
Prince, E., Finger, L. W. and Konnert, J. H.  International Tables for Crystallography (2006). Vol. C, Section 8.3.1.2, pp. 693-698 [ doi:10.1107/97809553602060000611 ]
... factors, and possibly higher cumulants of an atomic density function (Prince, 1994). The constrained calculation is usually performed by evaluating ... beta]13 = -[beta]23; one principal axis parallel to [110] , , , , , , , , , , , , , , , , , , , , , , , , , , , (e) [beta]11 = [beta]22, [beta]13 = [beta]23; one principal ... beta]13 = [beta]23; one principal axis parallel to [100] , , , , , , , , , , , , , , , , , (e) [beta]22 = 2[beta]12, [beta]23 = 0; one ...
     [more results from section 8.3.1 in volume C]

Constraints and restraints in refinement
Prince, E., Finger, L. W. and Konnert, J. H.  International Tables for Crystallography (2006). Vol. C, ch. 8.3, pp. 694-701 [ doi:10.1107/97809553602060000611 ]
... factors, and possibly higher cumulants of an atomic density function (Prince, 1994). The constrained calculation is usually performed by evaluating ... beta]13 = -[beta]23; one principal axis parallel to [110] , , , , , , , , , , , , , , , , , , , , , , , , , , , (e) [beta]11 = [beta]22, [beta]13 = [beta]23; one principal ... beta]13 = [beta]23; one principal axis parallel to [100] , , , , , , , , , , , , , , , , , (e) [beta]22 = 2[beta]12, [beta]23 = 0; one ...

Some examples
Prince, E. and Collins, D. M.  International Tables for Crystallography (2006). Vol. C, Section 8.2.3.2, pp. 691-692 [ doi:10.1107/97809553602060000610 ]
... Scaling by entropy maximization. Acta Cryst. A40, 705-708. Jaynes, E. T. (1979). Where do we stand on maximum entropy ...
     [more results from section 8.2.3 in volume C]

Robust/resistant methods
Prince, E. and Collins, D. M.  International Tables for Crystallography (2006). Vol. C, Section 8.2.2, pp. 689-691 [ doi:10.1107/97809553602060000610 ]
... by Tukey was applied to crystal structure refinement by Nicholson, Prince, Buchanan & Tucker (1982). It corresponds to a fitting function ... be introduced by this effect. References Belsley, D. A., Kuh, E. & Welsch, R. E. (1980). Regression diagnostics. New York: John Wiley. Box, ...

Maximum-likelihood methods
Prince, E. and Collins, D. M.  International Tables for Crystallography (2006). Vol. C, Section 8.2.1, p. 689 [ doi:10.1107/97809553602060000610 ]
Maximum-likelihood methods 8.2.1. Maximum-likelihood methods In Chapter 8.1 , structure refinement is presented as finding the answer to the question, `given a set of observations drawn randomly from populations whose means are given by a model, M(x), for some set of unknown parameters, x, how can we best determine ...

Other refinement methods
Prince, E. and Collins, D. M.  International Tables for Crystallography (2006). Vol. C, ch. 8.2, pp. 689-692 [ doi:10.1107/97809553602060000610 ]
... by Tukey was applied to crystal structure refinement by Nicholson, Prince, Buchanan & Tucker (1982). It corresponds to a fitting function ... to the model's correctness. References Belsley, D. A., Kuh, E. & Welsch, R. E. (1980). Regression diagnostics. New York: John Wiley. Box, ...

Software for least-squares calculations
Prince, E. and Boggs, P. T.  International Tables for Crystallography (2006). Vol. C, Section 8.1.7, p. 688 [ doi:10.1107/97809553602060000609 ]
Software for least-squares calculations 8.1.7. Software for least-squares calculations Giving even general recommendations on software is a difficult task for several reasons. Clearly, the selection of methods discussed in earlier sections contains implicitly some recommendations for approaches. Among the reasons for avoiding specifics are the following: (1) Assessing differences ...

Orthogonal distance regression
Prince, E. and Boggs, P. T.  International Tables for Crystallography (2006). Vol. C, Section 8.1.6, pp. 687-688 [ doi:10.1107/97809553602060000609 ]
... Stat. Comput. 8, 1052-1078. Boggs, P. T. & Rogers, J. E. (1990). Orthogonal distance regression. Contemporary mathematics: statistical analysis of ...

Conjugate-gradient methods
Prince, E. and Boggs, P. T.  International Tables for Crystallography (2006). Vol. C, Section 8.1.5.2, pp. 686-687 [ doi:10.1107/97809553602060000609 ]
Conjugate-gradient methods 8.1.5.2. Conjugate-gradient methods A numerical procedure that is applicable to large-scale problems that may not be sparse is called the conjugate-gradient method. Conjugate-gradient methods were originally designed to solve the quadratic minimization problem, find the minimum of where H is a symmetric, positive-definite ...
     [more results from section 8.1.5 in volume C]

Page: Previous 1 2 3 Next powered by swish-e
























































to end of page
to top of page