Discovering and Modeling the Driving Forces of Multidimensional Scales with Application to Financial Data

dc.contributor.author	M. Abdalla, Dr. Emtair
dc.date.accessioned	2024-11-21T18:44:11Z
dc.date.available	2024-11-21T18:44:11Z
dc.date.issued	2014-01-01
dc.identifier.issn	2518-5454
dc.identifier.uri	http://dspace-su.server.ly:8080/xmlui/handle/123456789/115
dc.description.abstract	In this paper, the driving forces are represented by linear and nonlinear principal components. In order to extract such forces, dimension reduction is applied using spectral decomposition technique. The most contributing lower order principal components are retained to represent the driving forces. The modeling of these forces is achieved in comparison to the Gaussian one.	en_US
dc.language.iso	other	en_US
dc.publisher	مجلة جامعة سرت العلمية (Susj)	en_US
dc.relation.ispartofseries	عدد 1;1-10
dc.subject	Descriptive tools، Gaussian distribution، Spectral decomposition، Dimension reduction، Driving Forces، principal components، modeling characteristics، skewness and kurtosis، Financial Factors	en_US
dc.title	Discovering and Modeling the Driving Forces of Multidimensional Scales with Application to Financial Data	en_US
dc.type	Article	en_US