A nonparametric regression cross spectrum for multivariate time series
We consider dependence structures in multivariate time series that are characterized by deterministic trends. Results from spectral analysis for stationary processes are extended to deterministic trend functions. A regression cross covariance and spectrum are defined. Estimation of these quantities is based on wavelet thresholding. The method is illustrated by a simulated example and a three-dimensional time series consisting of ECG, blood pressure and cardiac stroke volume measurements.
|Date of creation:||01 Jan 2008|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://cofe.uni-konstanz.de
More information through EDIRC
|Order Information:|| Web: http://cofe.uni-konstanz.de Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jan Beran & Yuanhua Feng, 1999. "Local Polynomial Estimation with a FARIMA-GARCH Error Process," CoFE Discussion Paper 99-08, Center of Finance and Econometrics, University of Konstanz.
When requesting a correction, please mention this item's handle: RePEc:knz:cofedp:0801. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ingmar Nolte)
If references are entirely missing, you can add them using this form.