A simple distribution-free algorithm for generating simulated high-dimensional correlated data with an autoregressive structure

Academic Article

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. © 2012 Copyright Taylor and Francis Group, LLC.
  • Digital Object Identifier (doi)

    Author List

  • Azuero A; Redden DT; Tiwari HK; Asmellash SG; Piyathilake CJ
  • Start Page

  • 89
  • Volume

  • 41