The DOI matches its Crossref record.
Projection Pursuit Regression
Open accessAbstract
A new method for nonparametric multiple regression is presented. The procedure models the regression surface as a sum of general smooth functions of linear combinations of the predictor variables in an iterative manner. It is more general than standard stepwise and stagewise regression procedures, does not require the definition of a metric in the predictor space, and lends itself to graphical interpretation.
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Cited by
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Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336
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Bengio, Y., Courville, A., & Vincent, P. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.50 · Cited by 13,001
Predictive habitat distribution models in ecology
Guisan, A., & Zimmermann, N. E. (2000) · Ecological Modelling · doi:10.1016/s0304-3800(00)00354-9 · Cited by 7,359
Friedman, J., Hastie, T., & Tibshirani, R. (2000) · The Annals of Statistics · doi:10.1214/aos/1016218223 · Cited by 6,884
Self-citationEfron, B., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013815 · Cited by 6,033
Metadata
- Authors
- Friedman, J. H., & Stuetzle, W.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1981-12
- Volume
- 76
- Issue
- 376
- Pages
- 817-823
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2091886411
- Cited by
- 2,216
- References
- 0
- FWCI
- 13.35
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Projection Pursuit Regression. https://app.cochat.ai/papers/10.1080/01621459.1981.10477729
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- Friedman, J. H., & Stuetzle, W. (1981). Projection Pursuit Regression. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1981.10477729
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
