NONPARAMETRIC ESTIMATION OF A GENERALIZED ADDITIVE MODEL WITH AN UNKNOWN LINK FUNCTION
By Joel L. Horowitz. 2001
119 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5d4f32ea1fe115c9129b6dfaaced38c174838260
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Liangjun Su
- S. Lee
- Aman Ullah
- Joel L. Horowitz
- Wenceslao González-Manteiga
- Annie Qu
- Lan Xue
- Jianhui Zhou
In Statistics and Probability
- Liangjun Su
- Wenceslao González-Manteiga
- S. Lee
- Joel L. Horowitz
- Aman Ullah
- Oliver B. Linton
- Lan Xue
- M. Febrero–Bande
Citations in the corpus
- The multinomial logit model revisited: A semi-parametric approach in discrete choice analysis (2011, background): “Ichimura (1993), Horowitz (2001), and Fosgerau (2006) investigated statistical inference for semiparametric models using the kernel density estimation method.”
- Generalized additive models for functional data (2013, background): “Some other alternatives are the Single Index Models (SIM) (see for example Horowitz, 1998, and references therein), and the GAM with an unknown link function (Horowitz, 2001), the latter nesting all the previous models.”
- Semiparametric Estimation of a Panel Data Proportional Hazards Model with Fixed Effects (2004, methodology): “The same type of scale normalization is used for a similar reason in Horowitz (2001).”
- Estimation of a semiparametric transformation model (2008, background): “Recently Ekeland, Heckman, and Nesheim (2004), building on ideas of Horowitz (1996, 2001) ,”
- Rate optimal estimation with the integration method in the presence of many covariates (2005, background): “For one, the estimates are readily interpretable as estimating the marginal impacts in any regression which, in (weak) separable models, is simply the separable component function (see [8,24,25]).”
- Local polynomial estimation of nonparametric simultaneous equations models (2008, methodology): “Once we obtain bb2, we follow the lead of Horowitz (2001) and set the data-driven choice of b1 to bebb1 ¼ bb2n ða a Þ=ð2g Þ, (2.16) where a , a and g are defined in (2.8).”
- Identification and estimation of local average derivatives in non-separable models without monotonicity (2009, unknown): “For related mean and quantile regression models with additive error terms , see also Christopeit and Hoderlein ( 2006 ) , Horowitz ( 2001 ) and Horowitz and Mammen ( 2007a , b ) .”
- Consistent Model Selection for Marginal Generalized Additive Model for Correlated Data (2010, methodology): “The theoretical technique for the spline approach is very different from the kernel approach (Horowitz 2001) for the generalized additive model.”