Robust estimation and inference for bivariate line-fitting in allometry.

@article{Taskinen2011RobustEA,
  title={Robust estimation and inference for bivariate line-fitting in allometry.},
  author={Sara Taskinen and David I. Warton},
  journal={Biometrical journal. Biometrische Zeitschrift},
  year={2011},
  volume={53 4},
  pages={
          652-72
        }
}
In allometry, bivariate techniques related to principal component analysis are often used in place of linear regression, and primary interest is in making inferences about the slope. We demonstrate that the current inferential methods are not robust to bivariate contamination, and consider four robust alternatives to the current methods -- a novel sandwich estimator approach, using robust covariance matrices derived via an influence function approach, Huber's M-estimator and the fast-and-robust… CONTINUE READING
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