Sparse partial least squares regression for on‐line variable selection with multivariate data streams

摘要

Abstract Data streams arise in several domains. For instance, in computational finance, several statistical applications revolve around the real-time discovery of associations between a very large number of co-evolving data feeds representing asset prices. The problem we tackle in this paper consists of learning a linear regression function from multivariate input and output streaming data in an incremental fashion while also performing dimensionality reduction and variable selection. When inpu.