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Semiparametric Regression Using Variational Approximation

Hui, Francis; You, Chong; Shang, Hanlin; Mueller, Samuel

Description

Semiparametric regression offers a flexible framework for modeling non-linear relationships between a response and covariates. A prime example are generalized additive models where splines (say) are used to approximate non-linear functional components in conjunction with a quadratic penalty to control for overfitting. Estimation and inference are then generally performed based on the penalized likelihood, or under a mixed model framework. The penalized likelihood framework is fast but...[Show more]

CollectionsANU Research Publications
Date published: 2019-02-27
Type: Journal article
URI: http://hdl.handle.net/1885/177000
Source: Journal of the American Statistical Association
DOI: 10.1080/01621459.2018.1518235
Access Rights: Open Access

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