Characterization of a Ranked-Set Sample with Application to Estimating Distribution Functions

1988 ◽  
Vol 83 (402) ◽  
pp. 374-381 ◽  
Author(s):  
S. Lynne Stokes ◽  
Thomas W. Sager
Keyword(s):  
Distribution Functions ◽  
Ranked Set Sample

scholarly journals Opacity distribution functions for stellar spectra synthesis

2019 ◽  
Vol 627 ◽  
pp. A157
Author(s):  
M. Cernetic ◽  
A. I. Shapiro ◽  
V. Witzke ◽  
N. A. Krivova ◽  
S. K. Solanki ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Synthesis ◽  
Distribution Functions ◽  
Transmission Curve ◽  
Spectral Interval ◽  
Space Telescopes ◽  
Radiative Fluxes ◽  
Stellar Spectra ◽  
Speed Up

Context. Stellar spectra synthesis is essential for the characterization of potential planetary hosts. In addition, comprehensive stellar variability calculations with fast radiative transfer are needed to disentangle planetary transits from stellar magnetically driven variability. The planet-hunting space telescopes, such as CoRoT, Kepler, and TESS, bring vast quantities of data, rekindling the interest in fast calculations of the radiative transfer. Aims. We revisit the opacity distribution functions (ODF) approach routinely applied to speed up stellar spectral synthesis. To achieve a considerable speedup relative to the state of the art, we further optimize the approach and search for the best ODF configuration. Furthermore, we generalize the ODF approach for fast calculations of flux in various filters often used in stellar observations. Methods. In a parameter-sweep fashion, we generated ODF in the spectral range from UV to IR with different setups. The most accurate ODF configuration for each spectral interval was determined. We adapted the wavelength grid based on the transmission curve for calculations of the radiative fluxes through filters before performing the normal ODF procedure. Results. Our optimum ODF configuration allows for a three-fold speedup, compared to the previously used ODF configurations. The ODF generalization to calculate fluxes through filters results in a speedup of more than two orders of magnitude.

On the multifractality of plasma turbulence in the solar wind

2019 ◽  
Vol 15 (S354) ◽  
pp. 371-374
Author(s):  
Sebastián Echeverría ◽  
Pablo S. Moya ◽  
Denisse Pastén
Keyword(s):  
Solar Wind ◽  
Velocity Distribution ◽  
Distribution Functions ◽  
Fluctuation Analysis ◽  
Magnetic Fluctuations ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Particle In Cell ◽  
Velocity Distribution Functions ◽  
Detrended Fluctuation

AbstractIn this work we have analyzed turbulent plasma in the kinetic scale by the characterization of magnetic fluctuations time series. Considering numerical Particle-In-Cell (PIC) simulations we apply a method known as MultiFractal Detrended Fluctuation Analysis (MFDFA) to study the fluctuations of solar-wind-like plasmas in thermodynamic equilibrium (represented by Maxwellian velocity distribution functions), and out of equilibrium plasma represented by Tsallis velocity distribution functions, characterized by the kappa (κ) parameter, to stablish relations between the fractality of magnetic fluctuation and the kappa parameter.

Evaluation of amorphous and crystalline SiC by extended energy loss fine structure (EXELFS) analysis

1988 ◽  
Vol 46 ◽  
pp. 466-467
Author(s):  
P. Angelini ◽  
P. S. Sklad ◽  
J. C. Sevely ◽  
D. K. Hssein
Keyword(s):  
Fine Structure ◽  
Amorphous Materials ◽  
Materials Science ◽  
Amorphous State ◽  
Near Neighbor ◽  
Distribution Functions ◽  
Radial Distribution Functions ◽  
Structural Ceramics ◽  
Amorphous Sic

Crystalline as well as amorphous forms of silicon carbide are materials which have important uses in many areas of materials science including structural ceramics, coatings, and semiconductors. The characterization of SiC by the use of the EXELFS technique yields radial distribution functions (RDF) which are sensitive to the structure and composition within near neighbor distances of either C or Si atoms. In this way a quantitative analysis of possible variations in “structure” can be made. EXELFS analyses of crystalline SiC are especially important in order to evaluate the method when comparison with results from the amorphous state are to be made. The EXELFS technique has previously been applied to study both crystalline as well as amorphous materials.Crystalline as well as amorphous SiC was evaluated. One specimen was a commercially available SiC single crystal. Two other specimens utilized a similar SiC starting material which had been made amorphous either by ion implantation with chromium or by irradiation from 300 kV electrons.

Determination of Structure, Shape and Sizes of Clusters Using Radial Distribution Functions (RDF) Method

1992 ◽  
Vol 272 ◽  
Author(s):  
Pavel E. Kolosov ◽  
A. V. Bubnov
Keyword(s):  
Distribution Functions ◽  
Structure Characterization ◽  
Radial Distribution Functions ◽  
Experimental Conditions ◽  
Interatomic Distances ◽  
X Ray ◽  
Molybdenum Sulfides ◽  
X Ray Scattering

ABSTRACTThe theoretical reduced intensity of X-ray scattering i(S) may be calculated for a cluster of any structure using Debye's formula. The comparison of both experimental determination and model calculation of the RDF or i(S) allows, to make a conclusions about structure of materials in a wide region of interatomic distances. This is a very important for direct structure characterization of giant clusters, dispersed molybdenum sulfides etc.. The simple formula for the upper limit of interatomic distances when the data are collected at equidistant step on S – scatterinrg vector, may be used for the optimal experimental conditions selection.

scholarly journals Extreme residual dependence for random vectors and processes

2011 ◽  
Vol 43 (01) ◽  
pp. 217-242 ◽  
Author(s):  
Laurens De Haan ◽  
Chen Zhou
Keyword(s):  
Stochastic Processes ◽  
Systemic Risk ◽  
Marginal Distribution ◽  
Banking System ◽  
Domain Of Attraction ◽  
Extreme Value Distribution ◽  
Distribution Functions ◽  
Two Dimensional ◽  
Higher Dimensional

A two-dimensional random vector in the domain of attraction of an extreme value distributionGis said to be asymptotically independent (i.e. in the tail) ifGis the product of its marginal distribution functions. Ledford and Tawn (1996) discussed a form of residual dependence in this case. In this paper we give a characterization of this phenomenon (see also Ramos and Ledford (2009)), and offer extensions to higher-dimensional spaces and stochastic processes. Systemic risk in the banking system is treated in a similar framework.

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