Downloads provided by UsageCounts
doi: 10.18452/3829
handle: 10419/66283
We consider the component analysis problem for a regression model with an additive structure. The problem is to check the hypothesis of linearity for each component without specifying the structure of the remaining components. In this paper we show that under mild conditions on the design and smoothness of the regression function, each component can be tested with the rate corresponding to the case if all the remaining components were known. The proposed procedure is based on the Haar transform and it is computationally straightforward.
nonparametric alternative, ddc:330, hypothesis of linearity, 330 Wirtschaft, Haar basis, 17 Wirtschaft, additive model,component analysis,Haar basis,hypothesis of linearity,nonparametric alternative,regression, component analysis, regression, additive model
nonparametric alternative, ddc:330, hypothesis of linearity, 330 Wirtschaft, Haar basis, 17 Wirtschaft, additive model,component analysis,Haar basis,hypothesis of linearity,nonparametric alternative,regression, component analysis, regression, additive model
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 124 | |
| downloads | 59 |

Views provided by UsageCounts
Downloads provided by UsageCounts