title: A Simple Distribution-Free Algorithm for Generating Simulated High-Dimensional Correlated Data with an Autoregressive Structure.
abstract: A distribution-free method to generate high-dimensional sequences of dependent variables with an autoregressive structure is presented. The quantile or fractile correlation (i.e., the moment correlation of the quantiles) is used as measure of dependence among a set of contiguous variables. The proposed algorithm breaks the sequence in small parts and avoids having to define one large correlation matrix for the entire high-dimensional sequence of variables. Simulations based on proteomics data are presented. Results suggest that negligible or no loss of fractile correlation occurs by splitting the generation of a sequence into small parts.
authors.affiliation: Department of Community Health Outcomes and Systems, University of Alabama at Birmingham, Birmingham, Alabama, USA.
authors.forename: Andres
authors.initials: A
authors.lastname: Azuero
authors.forename: David T
authors.initials: DT
authors.lastname: Redden
authors.forename: Hemant K
authors.initials: HK
authors.lastname: Tiwari
authors.forename: Senait G
authors.initials: SG
authors.lastname: Asmellash
authors.forename: Chandrika J
authors.initials: CJ
authors.lastname: Piyathilake
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