Signal Extraction: Efficient Estimation, 'Unit Root'-Tests and Early Detection of Turning Points - ISBN:3540229353

Signal Extraction: Efficient Estimation, 'Unit Root'-Tests and Early Detection of Turning Points

Date: 14 April 2011, 12:21

Free register and download UseNet downloader, then you can FREE Download from UseNet.

Download without Limit " Signal Extraction: Efficient Estimation, 'Unit Root'-Tests and Early Detection of Turning Points " from UseNet for FREE!

The book provides deep insights into the signal extraction problem - especially at the boundary of a sample, where asymmetric filters must be used - and how to solve it optimally. The traditional model-based approach (TRAMO/SEATS or X-12-ARIMA) is an inefficient estimation method because it relies on one-step ahead forecasting performances (of a model) whereas the signal extraction problem implicitly requires good multi-step ahead forecasts also. Unit roots are important properties of the input signal because they generate a set of constraints for the best extraction filter. Since traditional tests essentially rely on one-step ahead forecasting performances, new tests are presented here which implicitly account for multi-step ahead forecasting performances too. The gain in efficiency obtained by the new estimation method is analyzed in great detail, using simulated data as well as 'real world' time series.

Download Links:

Download Link (High Speed Download)

Download Link 1 (http://www.filesonic.com/...S)

Download Link 2 (http://depositfiles.com/...yyia0htil)

Download Link 3 (http://uploading.com/...Sign)

DISCLAIMER:

This site does not store Signal Extraction: Efficient Estimation, 'Unit Root'-Tests and Early Detection of Turning Points on its server. We only index and link to Signal Extraction: Efficient Estimation, 'Unit Root'-Tests and Early Detection of Turning Points provided by other sites. Please contact the content providers to delete Signal Extraction: Efficient Estimation, 'Unit Root'-Tests and Early Detection of Turning Points if any and email us, we'll remove relevant links or contents immediately.