On the performance of some ridge estimators in partially linear models with heteroskedastic and autocorrelated errors

dc.contributor.authorTabakan, Gülin
dc.contributor.authorTürkmen, Asuman S.
dc.date.accessioned13.07.201910:50:10
dc.date.accessioned2019-07-16T08:22:15Z
dc.date.available13.07.201910:50:10
dc.date.available2019-07-16T08:22:15Z
dc.date.issued2015
dc.departmentİktisadi ve İdari Bilimler Fakültesi
dc.description.abstractThis paper is concerned with a partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the nonlinear component with correlated and uncorrelated random errors. The estimation of covariance matrices of parameter estimates are modeled by Newey-West heteroscedasticity and autocorrelation consistent estimator when the errors are dependent. Real and simulated data sets are utilized to demonstrate the performance of the biased estimators. © 2015 Pakistan Journal of Statistics.
dc.identifier.endpage210en_US
dc.identifier.issn1012-9367
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ3
dc.identifier.startpage187en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12451/2513
dc.identifier.volume31en_US
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherISOSS Publications
dc.relation.ispartofPakistan Journal of Statistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAutocorrelation
dc.subjectConsistent Estimator
dc.subjectDifference-Based Estimator
dc.subjectHeteroscedasticity
dc.subjectMulticollinearity
dc.subjectPartially Linear Regression Model
dc.titleOn the performance of some ridge estimators in partially linear models with heteroskedastic and autocorrelated errors
dc.typeArticle

Files