| | |  | | | | Record from Web of Science® | | | | | | |
| MULTIVARIATE ADAPTIVE REGRESSION SPLINES |
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| Author(s): FRIEDMAN JH |
| Source: ANNALS OF STATISTICS Volume: 19 Issue: 1 Pages: 1-67 Published: MAR 1991 |
| Times Cited: 1,157 References: 48 |
| Abstract: A new method is presented for flexible regression modeling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number of basis functions as well as the parameters associated with each one (product degree and knot locations) are automatically determined by the data. This procedure is motivated by the recursive partitioning approach to regression and shares its attractive properties. Unlike recursive partitioning, however, this method produces continuous models with continuous derivatives. It has more power and flexibility to model relationships that are nearly additive or involve interactions in at most a few variables. In addition, the model can be represented in a form that separately identifies the additive contributions and those associated with the different multivariable interactions. |
| Document Type: Article |
| Language: English |
| Reprint Address: FRIEDMAN, JH (reprint author), STANFORD UNIV, DEPT STAT, SEQUOIA HALL, STANFORD, CA 94305 USA |
| Publisher: INST MATHEMATICAL STATISTICS, IMS BUSINESS OFFICE-SUITE 6 3401 INVESTMENT BLVD, HAYWARD, CA 94545 |
| Subject Category: Statistics & Probability |
| IDS Number: FF047 |
| ISSN: 0090-5364 |
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| | | | | | | | | Record from Web of Science® | | | | | | | | | |