Abstract.
In this paper, a number of robust biased estimators (e.g. ordinary robust ridge estimator, robust principal components estimator, robust combined principal components estimator, robust single-parametric principal components estimator, robust root-root estimator) are established by means of a unified expression of biased estimators and based on the principle of equivalent weight. The most attractive advantage of these new estimators is that they can not only overcome the ill-conditioning of the normal equation but also have the ability to resist outliers. A numerical example is used to illustrate that these new estimators are much better than the least-squares estimator and various biased estimators even when both ill-conditioning and outliers exist.
Similar content being viewed by others
Author information
Authors and Affiliations
Additional information
Received: 14 November 1995/Accepted: 11 February 1998
Rights and permissions
About this article
Cite this article
Gui, Q., Zhang, J. Robust biased estimation and its applications in geodetic adjustments. Journal of Geodesy 72, 430–435 (1998). https://doi.org/10.1007/s001900050182
Issue Date:
DOI: https://doi.org/10.1007/s001900050182