A Simple Distribution-Free Algorithm for Generating Simulated High-Dimensional Correlated Data with an Autoregressive Structure
DOI10.1080/03610918.2011.579368zbMath1489.62266OpenAlexW1997146993WikidataQ34079125 ScholiaQ34079125MaRDI QIDQ2905721
Senait G. Asmellash, Andres Azuero, David T. Redden, Chandrika J. Piyathilake, Hemant Kumar Tiwari
Publication date: 28 August 2012
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc3217303
Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Cites Work
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- A distribution-free approach to inducing rank correlation among input variables
- Linear Transformation to a Set of Stochastically Dependent Normal Variables
- On the Generation of Normal Random Vectors
- Rank Correlation and Tests of Significance Involving No Assumption of Normality
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