In particular, the method of least median of squares (LMS) has attracted attention. Its hallmark is high statistical resistance, which makes it immune to up to 50% contamination in the data. However, the same property makes it inefficient and can cause faulty fitting of typical fishery data....
The 2D Least Median of Squares (LMS) is a popular tool in robust regression because of its high breakdown point: up to half of the input data can be contaminated with outliers without affecting the accuracy of the LMS estimator. The complexity of 2D LMS estimation has been shown to be \...
This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re‐weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These ...
2. PROPERTIES OF THE LEAST MEDIAN Note that the breakdown point depends only slightly OF SQUARES METHOD on n. To have only a single value, one often considers the limit for n +w (with p fixed); so it can be said that We shall now investigate the behavior of the LMS tech- L S ...
Least median of squares regression presents a daunting computational problem for moderate to large data sets — the optimum is the Chebyshev regression fit to the correct subset of the cases, and finding it exactly requires an investigation of all subsets of the cases of a certain size. The fea...
Ordinary least squares (OLS) regression is relatively sensitive to the presence of outliers in a data set. In this paper, a robust estimation method, least median of squares (LMS) is used to identify outliers in land value data. Once the outliers are identified, are the land value equations...
最小均方(LMS) 4) median regression 中位数回归 1. A semiparametric procedure is proposed to estimate the parameter in nonlinearmedian regressionmodel with randomly right censored data. 研究了带有不完全数据的非线性模型的中位数回归问题。 2.
This study examines the performance of robust method of the least median squares (LMS) and the multi-stage method (MM) compared to OLS in a regression analysis of data which contains outliers. Data analysis was performed on simulation data and oil palm production data. Based on the average ...
Standard high breakdown criteria for the regression problem are the least median of squares (LMS) and least trimmed squares (LTS); those for the ... Douglas,M.,Hawkins,... - 《Computational Statistics & Data Analysis》 被引量: 147发表: 1999年 Sign-constrained robust least squares, subjective...
The proposed two-dimensional median least mean squares (TDMLMS) algorithm is a gradient-based steepest descent algorithm and employs the sample median of the instantaneous gradients within a suitable window as a measure of the true gradient. The nonlinear action of the median filtering operation ...