Online Decentralized Leverage Score Sampling for Streaming Multidimensional Time Series.

ABSTRACT: Estimating the dependence structure of multidimensional time series data in real-time is challenging. With large volumes of streaming data, the problem becomes more difficult when the multidimensional data are collected asynchronously across distributed nodes, which motivates us to sample representative data points from streams. We propose a leverage score sampling (LSS) method for efficient online inference of the streaming vector autoregressive (VAR) model. We define the leverage score for the streaming VAR model so that the LSS method selects informative data points in real-time with statistical guarantees of parameter estimation efficiency. Moreover, our LSS method can be directly deployed in an asynchronous decentralized environment, e.g., a sensor network without a fusion cent

SUBMITTER: Xie R 

PROVIDER: S-EPMC6556430 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature