A Method for Visualizing Multivariate Time Series Data
Download the Paper Forward to a colleague
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.
Subject Area:
Computation, Statistical Models
Suggested Citation:
Roger D. Peng, "A Method for Visualizing Multivariate Time Series Data" (February 2008). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 166.
http://www.bepress.com/jhubiostat/paper166