An Efficient Computation Strategy for Generalized Single-Index Models and Their Variants by Integrating With GAM.
Various generalizations of single-index models and associated estimation methods have been developed. However, implementing these developed methods requires much effort to program, case by case, due to the lack of a common and flexible vehicle to cover them. We suggest an efficient computation strat...
| Published in: | American Statistician Vol. 79; no. 3; pp. 302 - 311 |
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| Main Authors: | , , |
| Format: | Article |
| Published: |
Taylor & Francis Ltd
Aug2025
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=187004677&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 187004677 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: Aug2025 vid: 79 iid: 3 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 187004677 10.1080/00031305.2025.2464854 ppf: 302 ppct: 9 formats: tig: atl: An Efficient Computation Strategy for Generalized Single-Index Models and Their Variants by Integrating With GAM. aug: au: Li, Ximin Liang, Haozhe Liang, Hua affil: School of Mathematics and Statistics, Qingdao University, Shandong, China Department of Statistics and Finance, University of Science and Technology of China, Hefei, China Department of Statistics, George Washington University, Washington, DC su: Empirical research Electronic data processing Statistical models Nonlinear functions Computer performance Estimation theory sug: subj: Empirical research Electronic data processing Data Processing, Hosting, and Related Services Statistical models Nonlinear functions Computer performance Estimation theory keyword: Generalized additive models (GAM) Generalized partially linear single-index additive models (GPLSiAM) Generalized partially linear single-index models (GPLSiM) Generalized single-index models (GSiM) Penalized smoothing spline Generalized additive models (GAM) Generalized partially linear single-index additive models (GPLSiAM) Generalized partially linear single-index models (GPLSiM) Generalized single-index models (GSiM) Penalized smoothing spline ab: Various generalizations of single-index models and associated estimation methods have been developed. However, implementing these developed methods requires much effort to program, case by case, due to the lack of a common and flexible vehicle to cover them. We suggest an efficient computation strategy for easily estimating parameters and nonparametric functions in generalized single-index models and generalized partially linear single-index models by integrating with well-developed algorithms and packages for estimating the generalized additive models (Wood; Hastie and Tibshirani, GAM). Such an integration makes estimation in these index-type models much easier, expedient, and flexible and brings a lot of convenience. We briefly introduce the principle and extensively examine numerical performance for various scenarios. Numerical experiments indicate that the proposed strategy works well with finite sample sizes and is especially flexible to model structures. Finally, we analyze two real-data examples as an illustration. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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