In regression applications, the presence of nonlinearity and correlation among observa-tionsoffercomputationalchallengesnotonlyintraditionalsettingssuchasleastsquaresregression, but also (and especially) when the objective function is nonsmooth as in thecase of quantile regression. Methods are developed for the modelling and estimation ofnonlinearconditionalquantilefunctionswhendataareclusteredwithintwo levelnesteddesigns.TheproposedestimationalgorithmisablendofasmoothingalgorithmforquantileregressionandasecondorderLaplacianapproximationfornonlinearmixedmodels.Thisoptimization approach has the appealing advantage of reducing the original nonsmoothproblemtoanapproximatedL2problem.Whiletheestimationalgorithmisiterative,theobjectivefunctiontobeoptimizedhasasimpleanalyticform.Theproposedmethodsareassessed through a simulation study and two applications, one in pharmacokinetics andonerelatedtogrowthcurvemodellinginagriculture
Modelling and estimation of nonlinear quantile regression with clustered data / Geraci, M. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 136(2019), pp. 30-46. [10.1016/j.csda.2018.12.005]
Titolo: | Modelling and estimation of nonlinear quantile regression with clustered data | |
Autori: | ||
Data di pubblicazione: | 2019 | |
Rivista: | ||
Citazione: | Modelling and estimation of nonlinear quantile regression with clustered data / Geraci, M. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 136(2019), pp. 30-46. [10.1016/j.csda.2018.12.005] | |
Handle: | http://hdl.handle.net/11573/1463932 | |
Appartiene alla tipologia: | 01a Articolo in rivista |
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