## Neutron Scattering Data Analysis 1990: Invited and Contributed Papers from the Conference on Neutron Scattering Data Analysis Held at The Rutherford Appleton Laboratory, Chilton, 14-16 March 1990 |

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Page 7

From this we have the joint probability Pr(C, D) = Pr(C) Pi(D\C) = Pr(D) Pr(C|£>)

Exactly as usual, we use this to find Pt(D) = J dCPr(C,D) = J dCPr(C)Pr(D\C)

where dC = d(

choice of ...

From this we have the joint probability Pr(C, D) = Pr(C) Pi(D\C) = Pr(D) Pr(C|£>)

Exactly as usual, we use this to find Pt(D) = J dCPr(C,D) = J dCPr(C)Pr(D\C)

where dC = d(

**parameters**entering the matrix C) and thence to estimate ourchoice of ...

Page 119

Three levels of data analysis are available: • numerical analysis: this is the option

to use when no a priori information on the pattern is available (unknown cell

Three levels of data analysis are available: • numerical analysis: this is the option

to use when no a priori information on the pattern is available (unknown cell

**parameters**for instance) or when the pattern cannot be described in the ...Page 144

Full Reitveld refinements on all positional and anisotropic temperature

expected the third data set gave significantly different temperature

compared to ...

Full Reitveld refinements on all positional and anisotropic temperature

**parameters**were performed on the three differently normalized data sets. Asexpected the third data set gave significantly different temperature

**parameters**compared to ...

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algorithm applications approach atoms Bayesian beam Bragg peaks calculated configuration constraints coordinates corresponding cost function cross-section crystallographic Data Anal data analysis data set defined detector bank determined diffraction data diffractometer distribution function elastic scattering energy error bars example experiment experimental Figure Fourier transform Gaussian GENIE GENIE-V3 histogram inelastic instrument intensity inverse ISIS least squares likelihood function magnetic structure magnetisation density matrix MaxEnt reconstruction Maximum Entropy McGreevy measured method molecular Monte Carlo neutron diffraction neutron scattering normalisation normalization obtained optimisation optimization problems parameters Patterson map performed Phys plot positive powder diffraction presented at Neutron prior procedure quasielastic radial distribution functions refinement reflectivity data resolution function ROTAX Rutherford Appleton Laboratory sample scan scattering law shown simulated annealing single crystal solution spectra spectrometer spectrum statistical structure factor symmetry technique temperature time-of-flight truncation UNIRAS unit cell vanadium vector wavelength workspace