Results 1 to 10 of about 16,285 (243)
Fast and robust deconvolution of tumor infiltrating lymphocyte from expression profiles using least trimmed squares. [PDF]
PLoS Computational Biology, 2019 Gene-expression deconvolution is used to quantify different types of cells in a mixed population. It provides a highly promising solution to rapidly characterize the tumor-infiltrating immune landscape and identify cold cancers.
Yuning Hao +4 more
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Trimmed Least Squares Estimation in the Linear Model [PDF]
Journal of the American Statistical Association, 1980 Abstract We consider two methods of defining a regression analog to a trimmed mean. The first was suggested by Koenker and Bassett and uses their concept of regression quantiles. Its asymptotic behavior is completely analogous to that of a trimmed mean. The second method uses residuals from a preliminary estimator.
David Ruppert
exaly +4 more sources
Large Sample Behavior of the Least Trimmed Squares Estimator
MathematicsThe least trimmed squares (LTS) estimator is popular in location, regression, machine learning, and AI literature. Despite the empirical version of least trimmed squares (LTS) being repeatedly studied in the literature, the population version of the LTS ...
Yijun Zuo
doaj +3 more sources
Sediment Rating Curve Estimation Using Robust Regression [PDF]
فناوریهای پیشرفته در بهرهوری آب, 2022 A sediment rating curve is the most known method in the hydrological approach for suspended sediment load estimation that is a power equation (or linear equation based on logarithmic data transformation) to relate suspended sediment load to the river ...
Meysam Salarijazi +3 more
doaj +1 more source
On the least trimmed squares estimators for JS circular regression model
Kuwait Journal of Science, 2021 The least trimmed squares (LT S) estimation has been successfully used in the robust linear regression models. This paper, extends the LT S estimation to the JS circular regression model.
Shokrya Saleh Alshiqaq
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On the Least Trimmed Squares Estimator [PDF]
Algorithmica, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David M. Mount +4 more
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A Novel Reconstruction Method for Measurement Data Based on MTLS Algorithm
Sensors, 2020 Reconstruction methods for discrete data, such as the Moving Least Squares (MLS) and Moving Total Least Squares (MTLS), have made a great many achievements with the progress of modern industrial technology.
Tianqi Gu +3 more
doaj +1 more source
Computation of least squares trimmed regression--an alternative to least trimmed squares regression
, 2023 The least squares of depth trimmed (LST) residuals regression, proposed in Zuo and Zuo (2023) \cite{ZZ23}, serves as a robust alternative to the classic least squares (LS) regression as well as a strong competitor to the famous least trimmed squares (LTS) regression of Rousseeuw (1984) \cite{R84}.
Zuo, Yijun, Zuo, Hanwen
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Robust hybrid algorithms for regularization and variable selection in QSAR studies
Journal of Nigerian Society of Physical Sciences, 2023 This study introduces a robust hybrid sparse learning approach for regularization and variable selection. This approach comprises two distinct steps.
Christian N. Nwaeme, Adewale F. Lukman
doaj +1 more source
, 2000 Least trimmed squares (LTS) is a statistical technique for estimation of unknown parameters of a linear regression model and provides a “robust” alternative to the classical regression method based on minimizing the sum of squared residuals.
Čížek, Pavel, Víšek, Jan Ámos
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