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Least squares regression with errors in both variables: case studies
Química Nova, 2013 Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS).
Elcio Cruz de Oliveira +1 more
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Examining the Determinants of Foreign Direct Investment in BRICS
Journal of Accounting and Finance in Emerging Economies, 2022 Purpose: The study’s objectives were twofold. Firstly, to examine the determinants of foreign direct investment in BRICS (Brazil, Russia, India, China, South Africa).
Kunofiwa Tsaurai
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A Monte Carlo Comparison of Regression Estimators When the Error Distribution is Long-Tailed Symmetric [PDF]
, 2009 The performances of the ordinary least squares (OLS), modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares (WIN), trimmed least squares (TLS), Theil’s (Theil) and weighted Theil’s (Weighted Theil) estimators are ...
Mutan, Oya Can, Şenoğlu, Birdal
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Malaysian Journal of Social Sciences and Humanities (MJSSH), 2021 Real Estate is an asset that provides profitable investment in return. Commercial property constitutes an important part of the real estate sector. In valuing commercial property, rental value is an essential component for valuers in applying valuation methods.
Oliver Valentine Eboy, Avie Krista Jurah
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MODEL NON REKURSIF DALAM ANALISIS JALUR
Jurnal Matematika UNAND, 2020 Analisis jalur adalah suatu teknik penggambaran dan pengujian model hubungan antar variabel yang berbentuk sebab akibat, yang dikembangkan dari analisis regresi sebagai metode untuk mempelajari pengaruh langsung atau tidak langsung dari variabel bebas ...
DINIE ANEFI HAJARA +2 more
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MENGATASI PENCILAN PADA PEMODELAN REGRESI LINEAR BERGANDA DENGAN METODE REGRESI ROBUST PENAKSIR LMS
Barekeng, 2019 Ordinary Least Squares (OLS) is frequent used method for estimating parameters. OLS estimator is not a robust regression procedure for the presence of outliers, so the estimate becomes inappropriate.
Farida Daniel
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The comparative investigation of GWR and OLS methods in estimation of location models [PDF]
نشریه جغرافیا و برنامهریزی, 2018 Using the quantitative tools, methods and techniques in various sciences has been expanded during the recent years. The quantitative methods’ utilization in different branches of Humanities, especially the urban and regional planning have been always ...
Mohammadreza Pourmohammadi +2 more
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Comparison of straight line curve fit approaches for determining parameter variances and covariances
International Journal of Metrology and Quality Engineering, 2020 Pressure balances are known to have a linear straight line equation of the form y = ax + b that relates the applied pressure x to the effective area y, and recent work has investigated the use of Ordinary Least Squares (OLS), Weighted Least Squares (WLS),
Ramnath Vishal
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On the biased Two-Parameter Estimator to Combat Multicollinearity in Linear Regression Model
African Scientific Reports, 2022 The most popularly used estimator to estimate the regression parameters in the linear regression model is the ordinary least-squares (OLS). The existence of multicollinearity in the model renders OLS inefficient.
Janet Iyabo Idowu +3 more
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No penalty no tears: Least squares in high-dimensional linear models [PDF]
, 2016 Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable for problems with dimensionality larger than the sample size.
Dunson, David +2 more
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