Spline-backfitted kernel smoothing of partially linear additive model

By Shujie Ma, Lijian Yang. 2011

75 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c0f89a0886b3b5d1e7252ae620c22db37b852ce8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Hua Liang
2. Rong Chen
3. Heng Lian
4. Guang Cheng
5. Pang Du
6. Xin Chen
7. Jianyi Yang
8. Jing Wang

In Statistics and Probability

1. Heng Lian
2. Hua Liang
3. Rong Chen
4. Guang Cheng
5. Pang Du
6. Xin Chen
7. Jianyi Yang
8. Jing Wang

Citations in the corpus

• Varying Index Coefficient Models (2015, unknown): “…< 1 = ξN+q+1 = · · · = ξN+2q, where N increases along with the number of subjects n. Space Gn consists of functions, say , satisfying (i) is a polynomial of degree q − 1 on each of subintervals Is = [ξs, ξs+1), s = 0, . . . , Nn − 1, and INn = [ξNn, 1]; (ii) for q ≥ 2, function is q − 2 times…”
• Identification of Partially Linear Structure in Additive Models with an Application to Gene Expression Prediction from Sequences (2012, methodology): “For comparison, we compute the oracle estimator where we fit the true PLAM with five component functions, we also compute the sparse additive model where only the first penalty is used (and thus parametric components cannot be identified).”
• Oracally Efficient Two-Step Estimation of Generalized Additive Model (2013, unknown): “…(2006b), and Yang et al. (2006) for kernel methods; and more recently, the spline-backfitted kernel (SBK) smoothing methods of Wang and Yang (2007), Wang and Yang (2009), Liu and Yang (2010), and Ma and Yang (2011), and the spline-backfitted spline (SBS) smoothing method of Song and Yang (2010).”
• Semiparametric regression models with additive nonparametric components and high dimensional parametric components (2012, methodology): “Ma and Yang (2011) proposed a spline-backfitted kernel smoothing method for partially linear additive models which also contain a single nonparametric component and there is no sparsity enforced on the parametric part.”
• Determination of linear components in additive models (2011, methodology): “…additive models in Aerts, Claeskens, and Wand (2002), small area estimation in Opsomer, Claeskens, Ranalli, Kauermann, and Breidt (2008), and Spline-backfitted kernel smoothing for additive models in Wang and Yang (2007), Liu and Yang (2010), Ma and Yang (2011), and Song and Yang (2010).”