Multiple-point hit distribution functions and vague convergence of related measures

2011 ◽  
Vol 284 (8-9) ◽  
pp. 938-947 ◽  
Author(s):  
Felix Ballani
Keyword(s):  
Distribution Functions ◽  
Multiple Point ◽  
Vague Convergence

scholarly journals On the foundations of multivariate heavy-tail analysis

2004 ◽  
Vol 41 (A) ◽  
pp. 191-212 ◽  
Author(s):  
Sidney Resnick
Keyword(s):  
Heavy Tail ◽  
Distribution Functions ◽  
Dependence Structure ◽  
Regularly Varying Functions ◽  
Exploratory Technique ◽  
The Subject ◽  
Heavy Tailed ◽  
Japanese Yen ◽  
Vague Convergence ◽  
German Mark

Univariate heavy-tailed analysis rests on the analytic notion of regularly varying functions. For multivariate heavy-tailed analysis, reliance on functions is awkward because multivariate distribution functions are not natural objects for many purposes and are difficult to manipulate. An approach based on vague convergence of measures makes the differences between univariate and multivariate analysis evaporate. We survey the foundations of the subject and discuss statistical attempts to assess dependence of large values. An exploratory technique is applied to exchange rate return data and shows clear differences in the dependence structure of large values for the Japanese Yen versus German Mark compared with the French Franc versus the German Mark.

scholarly journals On the foundations of multivariate heavy-tail analysis

2004 ◽  
Vol 41 (A) ◽  
pp. 191-212 ◽  
Author(s):  
Sidney Resnick
Keyword(s):  
Heavy Tail ◽  
Distribution Functions ◽  
Dependence Structure ◽  
Regularly Varying Functions ◽  
Exploratory Technique ◽  
The Subject ◽  
Heavy Tailed ◽  
Japanese Yen ◽  
Vague Convergence ◽  
German Mark

Univariate heavy-tailed analysis rests on the analytic notion of regularly varying functions. For multivariate heavy-tailed analysis, reliance on functions is awkward because multivariate distribution functions are not natural objects for many purposes and are difficult to manipulate. An approach based on vague convergence of measures makes the differences between univariate and multivariate analysis evaporate. We survey the foundations of the subject and discuss statistical attempts to assess dependence of large values. An exploratory technique is applied to exchange rate return data and shows clear differences in the dependence structure of large values for the Japanese Yen versus German Mark compared with the French Franc versus the German Mark.

Computer processing of high-resolution images of periodic specimens

1986 ◽  
Vol 44 ◽  
pp. 2-5
Author(s):  
W. Chiu ◽  
M.F. Schmid ◽  
T.-W. Jeng
Keyword(s):  
High Resolution ◽  
Fourier Transforms ◽  
Complex Structure ◽  
Distribution Functions ◽  
Multiple Image ◽  
Cryo Electron Microscopy ◽  
Structure Factors ◽  
Unit Cells ◽  
High Resolution Images ◽  
Phase Probability Distribution

Cryo-electron microscopy has been developed to the point where one can image thin protein crystals to 3.5 Å resolution. In our study of the crotoxin complex crystal, we can confirm this structural resolution from optical diffractograms of the low dose images. To retrieve high resolution phases from images, we have to include as many unit cells as possible in order to detect the weak signals in the Fourier transforms of the image. Hayward and Stroud proposed to superimpose multiple image areas by combining phase probability distribution functions for each reflection. The reliability of their phase determination was evaluated in terms of a crystallographic “figure of merit”. Grant and co-workers used a different procedure to enhance the signals from multiple image areas by vector summation of the complex structure factors in reciprocal space.

Obtaining Normalized Atomic Radial Distribution Functions from EELFS Spectra

1997 ◽  
Vol 7 (C2) ◽  
pp. C2-577-C2-578 ◽  
Author(s):  
D. V. Surnin ◽  
D. E. Denisov ◽  
Yu. V. Ruts ◽  
P. M. Knjazev
Keyword(s):  
Radial Distribution ◽  
Distribution Functions ◽  
Radial Distribution Functions ◽  
Atomic Radial Distribution

Calculation of spatially inhomogeneous electron distribution functions

1998 ◽  
Vol 08 (PR7) ◽  
pp. Pr7-33-Pr7-42
Author(s):  
L. L. Alves ◽  
G. Gousset ◽  
C. M. Ferreira
Keyword(s):  
Electron Distribution ◽  
Distribution Functions ◽  
Spatially Inhomogeneous
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