|Publication type:||Article in scientific journal|
|Type of review:||Peer review (publication)|
|Title:||Nonparametric function estimation of the relationship between two repeatedly measured variables|
|Published in:||Statistica Sinica|
|Publisher / Ed. Institution:||Academia Sinica|
|Subjects:||Local quasi-likelihood estimator; Semiparametric estimation; Local linear regression|
|Subject (DDC):||500: Natural sciences and mathematics|
|Abstract:||We describe methods for estimating the regression function nonparametrically, and for estimating the variance components in a simple variance component model which is sometimes used for repeated measures data or data with a simple clustered structure. We consider a number of different ways of estimating the regression function. The main results are that the simple pooled estimator which treats the data as independent performs very well asymptotically, but that we can construct estimators which perform better asymptotically in some circumstances. The local linear version of the quasi-likelihood estimator is supposed to exploit the covariance structure of the model but does not in fact do so, asymptotically performing worse than the simple pooled estimator.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Data Analysis and Process Design (IDP)|
|Appears in Collections:||Publikationen School of Engineering|
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