Results 11 to 20 of about 16,285 (243)
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.
Andreas Alfons +2 more
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Kontinu: Jurnal Penelitian Didaktik Matematika, 2020 Tuberkulosis merupakan suatu penyakit menular yang disebabkan oleh bakteri Mycobacterium tuberculosis. Tuberkulosis sendiri menjadi salah satu penyakit yang menjadi perhatian dunia karena menjadi 10 penyebab kematian tertinggi di dunia pada tahun 2015 ...
Dina Rohmah +2 more
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Shield Tunnel Convergence Diameter Detection Based on Self-Driven Mobile Laser Scanning
Remote Sensing, 2022 The convergence diameter of shield tunnels is detected by ellipse fitting or local curve fitting to cross-section points. However, the tunnel section, which is extruded by an external force, has an irregular elliptical shape, and the waist of the tunnel ...
Lei Xu +6 more
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Models Where the Least Trimmed Squares and Least Median of Squares Estimators Are Maximum Likelihood [PDF]
SSRN Electronic Journal, 2019 The Least Trimmed Squares (LTS) and Least Median of Squares (LMS) estimators are popular robust regression estimators. The idea behind the estimators is to find, for a given h, a sub-sample of h 'good' observations among n observations and estimate the regression on that sub-sample.
Berenguer-Rico, V +2 more
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ISPRS International Journal of Geo-Information, 2021 Soil Moisture Deficit (SMD) is a key indicator of soil water content changes and is valuable to a variety of applications, such as weather and climate, natural disasters, agricultural water management, etc.
Prashant K. Srivastava +3 more
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Robust trimmed regression for heavy-tailed stable data: Competing methods and order statistics [PDF]
AUT Journal of Mathematics and ComputingRobust regression methods including, least trimmed squares, are among the most important methodologies for computing exact coefficient estimators when data is polluted with outliers.
Mohammad Bassam Shiekh Albasatneh +1 more
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UV3D: Underwater Video Stream 3D Reconstruction Based on Efficient Global SFM
Applied Sciences, 2022 With the increasing demand for underwater resource exploration, three-dimensional (3D) reconstruction technology is important for searching for lost underwater civilizations, underwater shipwrecks, or seabed structures.
Yanli Chen +4 more
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Estimasi Nonlinear Least Trimmed Squares (NLTS) pada Model Regresi Nonlinier yang Dikenai Outlier
Cauchy: Jurnal Matematika Murni dan Aplikasi, 2015 Constant Elasticity of Substitution (CES) production function is the intrinsic nonlinear regression models that are often used to estimate the data in an industry.
Nur Laili Arofah, Sri Harini
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On Robust Estimation of Error Variance in (Highly) Robust Regression
Measurement Science Review, 2020 The linear regression model requires robust estimation of parameters, if the measured data are contaminated by outlying measurements (outliers). While a number of robust estimators (i.e. resistant to outliers) have been proposed, this paper is focused on
Kalina Jan, Tichavský Jan
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Reweighted Least Trimmed Squares: An Alternative to One-Step Estimators [PDF]
SSRN Electronic Journal, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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