## 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 9

In particular, we can generate random samples f = f + Q-l/2g g being a

random vector with components drawn from the unit normal distribution. All this

can be accomplished equally well with the entropic prior, appropriate for postive /

.

In particular, we can generate random samples f = f + Q-l/2g g being a

**Gaussian**random vector with components drawn from the unit normal distribution. All this

can be accomplished equally well with the entropic prior, appropriate for postive /

.

Page 10

Since the results for the multiquadrics are visually identical to those of the

smooth, the optimal blur-width is large in each case. At an evidence value of

847db, ...

Since the results for the multiquadrics are visually identical to those of the

**Gaussian**, we only display the**Gaussian**and spline results. Because the data aresmooth, the optimal blur-width is large in each case. At an evidence value of

847db, ...

Page 49

Suppose also that the experimental data are the result of a convolution between

this scattering law and a

T of this

Suppose also that the experimental data are the result of a convolution between

this scattering law and a

**Gaussian**resolution function 7\exp(-x2/2w2). The heightT of this

**Gaussian**resolution function is determined by the length of time for ...### What people are saying - Write a review

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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