Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Roger Peng
Title: A Method for Visualizing Multivariate Time Series Data
Abstract: Visualization and exploratory analysis is an important part of any data analysis and is made more challenging when the data are voluminous and high-dimensional. One such example is environmental monitoring data, which are often collected over time and at multiple locations, resulting in a geographically indexed multivariate time series. Financial data, although not necessarily containing a geographic component, present another source of high-volume multivariate time series data. We present the mvtsplot function which provides a method for visualizing multivariate time series data. We outline the basic design concepts and provide some examples of its usage by applying it to a database of ambient air pollution measurements in the United States and to a hypothetical portfolio of stocks.

Page views:: 18946. Submitted: 2008-01-15. Published: 2008-03-31.
Paper: A Method for Visualizing Multivariate Time Series Data     Download PDF (Downloads: 22152)
mvtsplot.R: R source code Download (Downloads: 2873; 10KB)
v25c01.R: R code to reproduce the examples from the paper Download (Downloads: 2725; 4KB) Example data sets Download (Downloads: 2205; 2MB)

DOI: 10.18637/jss.v025.c01

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.