Results 1 to 10 of about 63,550 (174)
Sparse least trimmed squares regression [PDF]
SSRN Electronic Journal, 2011 Sparse model estimation is a topic of high importance in modern data analysis due to the increasing availability of data sets with a large number of variables. Another common problem in applied statistics is the presence of outliers in the data. This paper combines robust regression and sparse model estimation.
Alfons, Andreas +2 more
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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
doaj +2 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
doaj +1 more source
On the Least Trimmed Squares Estimator [PDF]
Algorithmica, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mount, David M. +4 more
openaire +2 more sources
Trimmed Least Square Estimators for Stable Ar(1) Processes [PDF]
Mathematica Pannonica, 2022 We prove the weak consistency of the trimmed least square estimator of the covariance parameter of an AR(1) process with stable errors.
Bazarova, Alina +2 more
openaire +3 more sources
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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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
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