Journal ArticleDOI
Robust regression using repeated medians
TLDR
The repeated median algorithm as mentioned in this paper is a robustified U-statistic in which nested medians replace the single mean and maintains the high 50% breakdown value and resist the effects of outliers even when they comprise nearly half of the data.Abstract:
: The repeated median algorithm is a robustified U-statistic in which nested medians replace the single mean. Unlike many generalizations of the univariate median, repeated median estimates maintain the high 50% breakdown value and can resist the effects of outliers even when they comprise nearly half of the data. Because they are calculated directly, not iteratively, repeated median procedures can be used as starting values for iterative robust estimation methods. For bivariate linear regression with symmetric errors, repeated median estimates are unbiased and Fisher consistent, and their efficiency under Gaussian sampling can be comparable to the efficiency of the univariate median. (Author)read more
Citations
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Journal ArticleDOI
Least Median of Squares Regression
TL;DR: In this paper, the median of the squared residuals is used to resist the effect of nearly 50% of contamination in the data in the special case of simple least square regression, which corresponds to finding the narrowest strip covering half of the observations.
Journal ArticleDOI
Extensions of the Procrustes Method for the Optimal Superimposition of Landmarks
F. James Rohlf,Dennis E. Slice +1 more
TL;DR: In this paper, a new method is presented that generalizes Siegel and Benson's (1982) resistant-fit theta-rho analysis so that more than two objects can be compared at the same time.
Journal ArticleDOI
Alternatives to the Median Absolute Deviation
TL;DR: In this article, the authors consider the median absolute deviation MAD n = 1.1926 med, {med j | xi − xj |} and the estimator Qn given by the.25 quantile of the distances {|xi − x j |; i < j}.
Book
Markov Random Field Modeling in Image Analysis
TL;DR: This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimisation.
Journal ArticleDOI
High breakdown-point and high efficiency robust estimates for regression
TL;DR: In this paper, a class of robust estimates for the linear model is introduced, called MM-estimates, which have simultaneously the following properties: (i) they are highly efficient when the errors have a normal distribution and (ii) their breakdown-point is 0.5.
References
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The Art of Computer Programming
TL;DR: The arrangement of this invention provides a strong vibration free hold-down mechanism while avoiding a large pressure drop to the flow of coolant fluid.
Journal ArticleDOI
Estimates of the Regression Coefficient Based on Kendall's Tau
TL;DR: In this article, a simple and robust estimator of regression coefficient β based on Kendall's rank correlation tau is studied, where the point estimator is the median of the set of slopes (Yj - Yi )/(tj-ti ) joining pairs of points with ti ≠ ti.
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TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
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Introduction to the Theory of Statistics.
Jacob Wolfowitz,A. M. Mood +1 more
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.