Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, LA | en_US |
dc.date.accessioned | 2019-04-02T05:58:41Z | - |
dc.date.available | 2019-04-02T05:58:41Z | - |
dc.date.issued | 1997-11-06 | en_US |
dc.identifier.issn | 0167-9473 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1016/S0167-9473(97)00018-2 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/149708 | - |
dc.description.abstract | Multivariate regression splines of arbitrary order assuming known knots using the additional function are developed. Model description and possible parameter tests for obtaining regression splines are also stated in detail for the triplicate case. A simulation study of drawn data from the Lubricant nonlinear regression model, where ''Lubricant'' is referred to lubricant data that we use in application, to compare the mean squares errors for the multivariate regression spline models and the multivariate polynomial models show the need of employing the multivariate regression splines in the approximation of the nonlinear regression models. (C) 1997 Elsevier Science B.V. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | multivariate regression spline | en_US |
dc.subject | piecewise polynomial | en_US |
dc.title | Multivariate regression splines | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1016/S0167-9473(97)00018-2 | en_US |
dc.identifier.journal | COMPUTATIONAL STATISTICS & DATA ANALYSIS | en_US |
dc.citation.volume | 26 | en_US |
dc.citation.spage | 71 | en_US |
dc.citation.epage | 82 | en_US |
dc.contributor.department | 統計學研究所 | zh_TW |
dc.contributor.department | Institute of Statistics | en_US |
dc.identifier.wosnumber | WOS:A1997YL35300005 | en_US |
dc.citation.woscount | 3 | en_US |
Appears in Collections: | Articles |