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                                       Details van artikel 14 van 25 gevonden artikelen
 
 
  Estimation of Parameters in Heteroscedastic Multiple Regression Model using Leverage Based Near-Neighbors
 
 
Titel: Estimation of Parameters in Heteroscedastic Multiple Regression Model using Leverage Based Near-Neighbors
Auteur: H. Midi
S. Rana
A.H.M.R. Imon
Verschenen in: Journal of applied sciences
Paginering: Jaargang 9 (2009) nr. 22 pagina's 4013-4019
Jaar: 2009
Inhoud: In this study, we propose a Leverage Based Near-Neighbor (LBNN) method where prior information on the structure of the heteroscedastic error is not required. In the proposed LBNN method, weights are determined not from the near-neighbor values of the explanatory variables, but from their corresponding leverage values so that it can be readily applied to a multiple regression model. Both the empirical and Monte Carlo simulation results show that the LBNN method offers substantial improvement over the existing methods. The LBNN has significantly reduced the standard errors of the estimates and also the standard errors of residuals for both simple and multiple linear regression models. Hence, the LBNN can be established as one reliable alternative approach to other existing methods that deal with heteroscedastic errors when the form of heteroscedasticity is unknown.
Uitgever: Asian Network for Scientific Information (provided by DOAJ)
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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