An evaluation of bootstrap methods for outlier detection in least squares regression

ISSN： 1360-0532

Source： Journal of Applied Statistics, Vol.33, Iss.7, 2006-08, pp. : 703-720

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

On least-squares bias in the AR(p) models: Bias correction using the bootstrap methods

By Tanizaki Hisashi Hamori Shigeyuki Matsubayashi Yoichi

Statistical Papers, Vol. 47, Iss. 1, 2006-01 ,pp. : 109-124

Springer Publishing Company

Access to resources Recommend Favorite

Outlier Detection Using Nonconvex Penalized Regression

By She Yiyuan Owen Art B.

Journal of the American Statistical Association, Vol. 106, Iss. 494, 2011-06 ,pp. : 626-639

Taylor & Francis Ltd

Access to resources Recommend Favorite

A Novel Regression Approach: Least Squares Ratio

By Akbilgic Oguz

Communications in Statistics: Theory and Methods, Vol. 38, Iss. 9, 2009-01 ,pp. : 1539-1545

Taylor & Francis Ltd

Access to resources Recommend Favorite

Quantile regression via iterative least squares computations

By Muggeo Vito M.R. Sciandra Mariangela Augugliaro Luigi

Journal of Statistical Computation and Simulation, Vol. 82, Iss. 11, 2012-11 ,pp. : 1557-1569

Taylor & Francis Ltd

Access to resources Recommend Favorite

The Degrees of Freedom of Partial Least Squares Regression

By Krämer Nicole Sugiyama Masashi

Journal of the American Statistical Association, Vol. 106, Iss. 494, 2011-06 ,pp. : 697-705

Taylor & Francis Ltd

Access to resources Recommend Favorite