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High dimensional structured additive regression models: Bayesian regularization, smoothing and predictive performance
Kneib, Thomas; Konrath, Susanne; Fahrmeir, Ludwig - In: Journal of the Royal Statistical Society Series C 60 (2011) 1, pp. 51-70
Persistent link: https://www.econbiz.de/10009215965
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Estimating the relationship between women's education and fertility in Botswana by using an instrumental variable approach to semiparametric expectile regression
Sobotka, Fabian; Radice, Rosalba; Marra, Giampiero; … - In: Journal of the Royal Statistical Society Series C 62 (2013) 1, pp. 25-45
Persistent link: https://www.econbiz.de/10010642033
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Bayesian geoadditive sample selection models
Wiesenfarth, Manuel; Kneib, Thomas - In: Journal of the Royal Statistical Society Series C 59 (2010) 3, pp. 381-404
Sample selection models attempt to correct for non-randomly selected data in a two-model hierarchy where, on the first level, a binary selection equation determines whether a particular observation will be available for the second level, i.e. in the outcome equation. Ignoring the non-random...
Persistent link: https://www.econbiz.de/10008671163
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Generalized additive models for location, scale and shape for high dimensional data—a flexible approach based on boosting
Mayr, Andreas; Fenske, Nora; Hofner, Benjamin; Kneib, Thomas - In: Journal of the Royal Statistical Society Series C 61 (2012) 3, pp. 403-427
Persistent link: https://www.econbiz.de/10011033966