Matches in SemOpenAlex for { <https://semopenalex.org/work/W2893710115> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2893710115 abstract "SummaryPrediction is often the primary goal of data analysis. In this work, we propose a novel model averaging approach to the prediction of a functional response variable. We develop a crossvalidation model averaging estimator based on functional linear regression models in which the response and the covariate are both treated as random functions. We show that the weights chosen by the method are asymptotically optimal in the sense that the squared error loss of the predicted function is as small as that of the infeasible best possible averaged function. When the true regression relationship belongs to the set of candidate functional linear regression models, the averaged estimator converges to the true model and can estimate the regression parameter functions at the same rate as under the true model. Monte Carlo studies and a data example indicate that in most cases the approach performs better than model selection." @default.
- W2893710115 created "2018-10-05" @default.
- W2893710115 creator A5022087178 @default.
- W2893710115 creator A5046173951 @default.
- W2893710115 creator A5067460359 @default.
- W2893710115 date "2018-09-26" @default.
- W2893710115 modified "2023-10-14" @default.
- W2893710115 title "Functional prediction through averaging estimated functional linear regression models" @default.
- W2893710115 cites W16794263 @default.
- W2893710115 cites W1969842547 @default.
- W2893710115 cites W1985896026 @default.
- W2893710115 cites W2010647378 @default.
- W2893710115 cites W2033779771 @default.
- W2893710115 cites W2038580754 @default.
- W2893710115 cites W2046835809 @default.
- W2893710115 cites W2056592727 @default.
- W2893710115 cites W2067165060 @default.
- W2893710115 cites W2073738917 @default.
- W2893710115 cites W2085579733 @default.
- W2893710115 cites W2095194401 @default.
- W2893710115 cites W2108443364 @default.
- W2893710115 cites W2111598468 @default.
- W2893710115 cites W2125251038 @default.
- W2893710115 cites W2144148350 @default.
- W2893710115 cites W2150204378 @default.
- W2893710115 cites W2168175751 @default.
- W2893710115 cites W2208430066 @default.
- W2893710115 cites W28412257 @default.
- W2893710115 cites W3124798525 @default.
- W2893710115 cites W4241897277 @default.
- W2893710115 cites W4243797702 @default.
- W2893710115 cites W4292156489 @default.
- W2893710115 cites W611353362 @default.
- W2893710115 cites W621923488 @default.
- W2893710115 cites W649348608 @default.
- W2893710115 doi "https://doi.org/10.1093/biomet/asy041" @default.
- W2893710115 hasPublicationYear "2018" @default.
- W2893710115 type Work @default.
- W2893710115 sameAs 2893710115 @default.
- W2893710115 citedByCount "6" @default.
- W2893710115 countsByYear W28937101152019 @default.
- W2893710115 countsByYear W28937101152020 @default.
- W2893710115 countsByYear W28937101152021 @default.
- W2893710115 countsByYear W28937101152023 @default.
- W2893710115 crossrefType "journal-article" @default.
- W2893710115 hasAuthorship W2893710115A5022087178 @default.
- W2893710115 hasAuthorship W2893710115A5046173951 @default.
- W2893710115 hasAuthorship W2893710115A5067460359 @default.
- W2893710115 hasConcept C105795698 @default.
- W2893710115 hasConcept C28826006 @default.
- W2893710115 hasConcept C33923547 @default.
- W2893710115 hasConcept C48921125 @default.
- W2893710115 hasConcept C51820054 @default.
- W2893710115 hasConcept C64946054 @default.
- W2893710115 hasConcept C83546350 @default.
- W2893710115 hasConceptScore W2893710115C105795698 @default.
- W2893710115 hasConceptScore W2893710115C28826006 @default.
- W2893710115 hasConceptScore W2893710115C33923547 @default.
- W2893710115 hasConceptScore W2893710115C48921125 @default.
- W2893710115 hasConceptScore W2893710115C51820054 @default.
- W2893710115 hasConceptScore W2893710115C64946054 @default.
- W2893710115 hasConceptScore W2893710115C83546350 @default.
- W2893710115 hasLocation W28937101151 @default.
- W2893710115 hasOpenAccess W2893710115 @default.
- W2893710115 hasPrimaryLocation W28937101151 @default.
- W2893710115 hasRelatedWork W1541739370 @default.
- W2893710115 hasRelatedWork W2080398516 @default.
- W2893710115 hasRelatedWork W2094764829 @default.
- W2893710115 hasRelatedWork W2106328306 @default.
- W2893710115 hasRelatedWork W2167660240 @default.
- W2893710115 hasRelatedWork W2372618793 @default.
- W2893710115 hasRelatedWork W2970478921 @default.
- W2893710115 hasRelatedWork W2972137283 @default.
- W2893710115 hasRelatedWork W4226085254 @default.
- W2893710115 hasRelatedWork W1954208574 @default.
- W2893710115 isParatext "false" @default.
- W2893710115 isRetracted "false" @default.
- W2893710115 magId "2893710115" @default.
- W2893710115 workType "article" @default.