Point-process principal components analysis via geometric optimization
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
Journal
Volume
25
Issue
1
Pages
101 - 122
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