Results 221 to 230 of about 544,201 (272)

A random least-trimmed-squares identification algorithm

Automatica, 2003
The least-trimmed-squares (LTS) estimator is a robust estimator in terms of protecting the estimate from the outliers, but it possesses a high computational complexity. The author proposes a random LTS algorithm having a low computational complexity and that can be calculated a priori as a function of the required error bound and the confidence ...
Er-Wei Bai
exaly   +2 more sources

Least Trimmed Squares for Regression Models with Stable Errors

Fluctuation and Noise Letters, 2023
Least Trimmed Squares (LTS) is a robust regression method with respect to outliers. It is based on performing Ordinary Least Squares (OLS) estimates on sub-datasets and determining the optimal solution corresponding to the minimum sum of squared residuals. Since the method of LTS is based on OLS, errors in regression models have finite variance.
Mohammad Bassam Shiekh Albasatneh, Adel Mohammadpour   +1 more
openaire   +2 more sources

Adaptive choice of trimming proportion in trimmed least-squares estimation

Statistics and Probability Letters, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yadolah Dodge, Jana Jurečková
exaly   +3 more sources

A robust weighted least squares support vector regression based on least trimmed squares

Neurocomputing, 2015
In order to improve the robustness of the classcial LSSVM when dealing with sample points in the presence of outliers, we have developed a robust weighted LSSVM (reweighted LSSVM) based on the least trimmed squares technique (LTS). The procedure of the reweighted LSSVM includes two stages, respectively used to increase the robustness and statistical ...
Chuanfa Chen, Changqing Yan
exaly   +2 more sources

Multivariate least-trimmed squares regression estimator

Computational Statistics and Data Analysis, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
exaly   +2 more sources

The influence functions for the least trimmed squares and the least trimmed absolute deviations estimators

Statistics and Probability Letters, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
exaly   +3 more sources

Sparse Principal Component Analysis Based on Least Trimmed Squares

Technometrics, 2019
Sparse principal component analysis (PCA) is used to obtain stable and interpretable principal components (PCs) from high-dimensional data.
Yixin Wang, Stefan Van Aelst
openaire   +2 more sources

Application of the least trimmed squares technique to prototype-based clustering

Pattern Recognition Letters, 1996
Prototype-based clustering algorithms such as the K-means and the Fuzzy C-Means algorithms are sensitive to noise and outliers. This paper shows how the Least Trimmed Squares technique can be incorporated into prototype-based clustering algorithms to make them robust.
Raghu Krishnapuram, Rajesh Dave
exaly   +2 more sources

Least Median of Squares (LMS) and Least Trimmed Squares (LTS) Fitting for the Weighted Arithmetic Mean

International Conference on Information Processing and Management of Uncertainty, 2018
We look at different approaches to learning the weights of the weighted arithmetic mean such that the median residual or sum of the smallest half of squared residuals is minimized. The more general problem of multivariate regression has been well studied in statistical literature, however in the case of aggregation functions we have the restriction on ...
Gleb Beliakov, Marek Gagolewski, Simon James   +2 more
openaire   +2 more sources

Low-overlap point cloud registration algorithm based on variable-length least trimmed squares

Other Conferences, 2023
Point cloud registration is a key technology in point cloud processing, aiming to align two point clouds by estimating the optimal rigid transformation matrix.
Guangyuan Liu, Aijun Zhang
semanticscholar   +1 more source