Authors: Troschke, Sven-Oliver
Title: A Simulation Study To Compare Various Covariance Adjustment Techniques
Language (ISO): en
Abstract: A common procedure when combining two multivariate unbiased estimates (or forecasts) is the covariance adjustment technique (CAT). Here the optimal combination weights depend on the covariance structure of the estimators. In practical applications, however, this covariance structure is hardly ever known and, thus, has to be estimated. An effect of this drawback may be that the theoretically best method is no longer the best. In a simulation study (using normally distributed data) three different variants of CAT are compared with respect to their accuracy. These variants are different in the portion of the covariance structure that is estimated. We characterize which variant is appropriate in different situations and quantify the gains and losses that occur.
Subject Headings: combination of multivariate estimators
covariance adjustment technique
URI: http://hdl.handle.net/2003/4930
http://dx.doi.org/10.17877/DE290R-5427
Issue Date: 1999
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

Files in This Item:
File Description SizeFormat 
99_41.pdfDNB220.92 kBAdobe PDFView/Open
tr41-99.ps243.31 kBPostscriptView/Open


This item is protected by original copyright



All resources in the repository are protected by copyright.