Point-process principal components analysis via geometric optimization

Volume: 25, Issue: 1, Pages: 101 - 122
Published: Jan 1, 2013
Abstract
There has been a fast-growing demand for analysis tools for multivariate point-process data driven by work in neural coding and, more recently, high-frequency finance. Here we develop a true or exact as opposed to one based on time binning principal components analysis for preliminary processing of multivariate point processes. We provide a maximum likelihood estimator, an algorithm for maximization involving steepest ascent on two Stiefel...
Paper Details
Title
Point-process principal components analysis via geometric optimization
Published Date
Jan 1, 2013
Volume
25
Issue
1
Pages
101 - 122
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.