Matches in SemOpenAlex for { <https://semopenalex.org/work/W2067393664> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W2067393664 endingPage "799" @default.
- W2067393664 startingPage "787" @default.
- W2067393664 abstract "For estimation of linear models with randomly censored data, a class of data transformations is used to construct synthetic data. It is shown that the conditional variance of the synthetic data depends on the covariates in the model regardless of the homoscedasticity of the error. Therefore, linear models based on the synthetic data are always heteroscedastic models. To improve efficiency, we propose a weighted least squares (WLS) method, where the conditional variance of the synthetic data is estimated nonparametrically, then the standard WLS principle is applied to the synthetic data in the estimation procedure. The resultant estimator is asymptotically normal and the limiting variance is estimated using the plug-in method. In general, the proposed method improves the existing synthetic data methods for censored linear models, and gains more efficiency. For the censored heteroscedastic linear models, where the Buckley–James (BJ) and rank-based methods cannot be used since the condition of homoscedastic errors is violated, the new method provides a solution for better estimation. Monte Carlo simulations are conducted to compare the proposed method with the unweighted least squares method and the BJ method under different error conditions." @default.
- W2067393664 created "2016-06-24" @default.
- W2067393664 creator A5065562860 @default.
- W2067393664 creator A5086389905 @default.
- W2067393664 date "2009-10-01" @default.
- W2067393664 modified "2023-10-03" @default.
- W2067393664 title "Weighted least squares method for censored linear models" @default.
- W2067393664 cites W1970821996 @default.
- W2067393664 cites W1978357752 @default.
- W2067393664 cites W2031786162 @default.
- W2067393664 cites W2035196103 @default.
- W2067393664 cites W2041638842 @default.
- W2067393664 cites W2047522285 @default.
- W2067393664 cites W2049626087 @default.
- W2067393664 cites W2058952802 @default.
- W2067393664 cites W2059331042 @default.
- W2067393664 cites W2067012280 @default.
- W2067393664 cites W2068745974 @default.
- W2067393664 cites W2078793132 @default.
- W2067393664 cites W2083972068 @default.
- W2067393664 cites W2107368116 @default.
- W2067393664 cites W4241079352 @default.
- W2067393664 cites W4241284370 @default.
- W2067393664 doi "https://doi.org/10.1080/10485250902795636" @default.
- W2067393664 hasPublicationYear "2009" @default.
- W2067393664 type Work @default.
- W2067393664 sameAs 2067393664 @default.
- W2067393664 citedByCount "3" @default.
- W2067393664 countsByYear W20673936642012 @default.
- W2067393664 countsByYear W20673936642023 @default.
- W2067393664 crossrefType "journal-article" @default.
- W2067393664 hasAuthorship W2067393664A5065562860 @default.
- W2067393664 hasAuthorship W2067393664A5086389905 @default.
- W2067393664 hasConcept C101104100 @default.
- W2067393664 hasConcept C104409967 @default.
- W2067393664 hasConcept C105795698 @default.
- W2067393664 hasConcept C119043178 @default.
- W2067393664 hasConcept C163175372 @default.
- W2067393664 hasConcept C185429906 @default.
- W2067393664 hasConcept C188649462 @default.
- W2067393664 hasConcept C28826006 @default.
- W2067393664 hasConcept C33923547 @default.
- W2067393664 hasConcept C9936470 @default.
- W2067393664 hasConceptScore W2067393664C101104100 @default.
- W2067393664 hasConceptScore W2067393664C104409967 @default.
- W2067393664 hasConceptScore W2067393664C105795698 @default.
- W2067393664 hasConceptScore W2067393664C119043178 @default.
- W2067393664 hasConceptScore W2067393664C163175372 @default.
- W2067393664 hasConceptScore W2067393664C185429906 @default.
- W2067393664 hasConceptScore W2067393664C188649462 @default.
- W2067393664 hasConceptScore W2067393664C28826006 @default.
- W2067393664 hasConceptScore W2067393664C33923547 @default.
- W2067393664 hasConceptScore W2067393664C9936470 @default.
- W2067393664 hasIssue "7" @default.
- W2067393664 hasLocation W20673936641 @default.
- W2067393664 hasOpenAccess W2067393664 @default.
- W2067393664 hasPrimaryLocation W20673936641 @default.
- W2067393664 hasRelatedWork W2018351274 @default.
- W2067393664 hasRelatedWork W2067393664 @default.
- W2067393664 hasRelatedWork W2091673004 @default.
- W2067393664 hasRelatedWork W2110424642 @default.
- W2067393664 hasRelatedWork W2140312996 @default.
- W2067393664 hasRelatedWork W2612819891 @default.
- W2067393664 hasRelatedWork W3085066906 @default.
- W2067393664 hasRelatedWork W3123870899 @default.
- W2067393664 hasRelatedWork W3124819783 @default.
- W2067393664 hasRelatedWork W1861578010 @default.
- W2067393664 hasVolume "21" @default.
- W2067393664 isParatext "false" @default.
- W2067393664 isRetracted "false" @default.
- W2067393664 magId "2067393664" @default.
- W2067393664 workType "article" @default.