Descriptor

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Descriptor

A variable describing assets, used as an element of a risk index. For example, a volatility risk index, distinguishing high volatility assets from low volatility assets, could consist of several descriptors based on short term volatility, long term volatility, systematic and residual volatility, etc.
Copyright © 2012, Campbell R. Harvey. All Rights Reserved.
References in periodicals archive ?
Based on this representation, the model obtained by the application of OS-SVM is superior to previous models in two aspects: the strong correlation between the value of EC50 and the descriptors (R2 = 0.8662), the nature of the selected descriptors and information carried by these selected descriptors, and, finally, the high predictive power of Q2ext (0.8769).
It is interesting to observe that the SMD solvation model is powerful enough to allow discriminating between the values for the global descriptors in both solvents.
After that, the principal component analysis (PCA) was used to determine the nonlinearity and non-multicollinearity among variables and to select descriptors that correlate with the activity.
where [X.sub.i] is the value of each descriptor for a given molecule and [X.sub.max] and [X.sub.min] are the maximum and minimum value for each column of descriptors X.
Some of this literature that looks at the language of performance descriptors focuses on the content of the rubrics.
You should consider interactive elements and content descriptors as carefully as age appropriateness when deciding if a game is right for your child.
TNM descriptors of the new 8th edition with pictorial illustrations and main concern on imaging staging
Prior to the descriptors' calculation, the structures were subjected to CORINA, which is often used to create 3D structures of typically drug-like molecules.
"By diving deeper into storylines and characters and assigning much more granular metadata to content, Gracenote Video Descriptors give TV providers powerful datasets enabling fresher discovery, recommendation and voice experiences that satisfy the full spectrum of viewer tastes or moods."
One major aspect of the above local descriptors, including LBP, LDP, LDN, LPTP, and PTP is the generation of code histogram, where the face image is divided into p x q uniform regions (grids).
Trained sensory panelists using quantitative descriptive analysis assessed the intensity of the 10 descriptors. The results showed that principal component analysis explained 64% of data variability, with correlations found between foam-related descriptors from the sensory analysis and the robotic pourer, such as a positive and significant correlation between carbon dioxide and carbonation mouthfeel, the correlation of viscosity to sensory, and the maximum volume of foam and total lifetime of foam.