Chatterjee, Snigdhansu ; Bose, Arup (2000) Variance estimation in high dimensional regression models Statistica Sinica, 10 . pp. 497-515. ISSN 1017-0405
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Abstract
We treat the problem of variance estimation of the least squares estimate of the parameter in high dimensional linear regression models by using the Uncorrelated Weights Bootstrap (UBS). We find a representation of the UBS dispersion matrix and show that the bootstrap estimator is consistent if p2/n→ 0 where p is the dimension of the parameter and n is the sample size. For fixed dimension we show that the UBS belongs to the R-class as defined in Liu and Singh (1992).
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Academia Sinica, Institute of Statistical Science. |
| Keywords: | Bootstrap; Dimension Asymptotics; Jackknife; Many Parameter Regression; Variance Estimation |
| ID Code: | 93956 |
| Deposited On: | 30 Jun 2012 12:57 |
| Last Modified: | 19 May 2016 06:53 |
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