Asymptotics with increasing dimension for robust regression with applications to the bootstrap
A stochastic expansion for MMM-estimates in linear models with many parameters is derived under the weak condition κn1/3(logn)2/3→0κn1/3(logn)2/3→0\kappa n^{1/3}(\log n)^{2/3} \rightarrow 0, where nnn is the sample size and κκ\kappa the maximal diagonal element of the hat matrix. The expansion is u...
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
1989
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| In: |
The annals of statistics
Year: 1989, Jahrgang: 17, Heft: 1, Pages: 382-400 |
| ISSN: | 2168-8966 |
| DOI: | 10.1214/aos/1176347023 |
| Online-Zugang: | Volltext Volltext Volltext 
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| Verfasserangaben: | Enno Mammen |
| Zusammenfassung: | A stochastic expansion for MMM-estimates in linear models with many parameters is derived under the weak condition κn1/3(logn)2/3→0κn1/3(logn)2/3→0\kappa n^{1/3}(\log n)^{2/3} \rightarrow 0, where nnn is the sample size and κκ\kappa the maximal diagonal element of the hat matrix. The expansion is used to study the asymptotic distribution of linear contrasts and the consistency of the bootstrap. In particular, it turns out that bootstrap works in cases where the usual asymptotic approach fails. |
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| Beschreibung: | First available in Project Euclid: 12 April 2007 Gesehen am 01.03.2018 |
| Beschreibung: | Online Resource |
| ISSN: | 2168-8966 |
| DOI: | 10.1214/aos/1176347023 |