Approximated Uncertainty Propagation of Correlated Independent Variables Using the Ordinary Least Squares Estimator [PDF]
MoleculesFor chemical measurements, calibration is typically conducted by regression analysis. In many cases, generalized approaches are required to account for a complex-structured variance–covariance matrix of (in)dependent variables. However, in the particular
Jeong Sik Lim +2 more
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A New Convex Estimator Combining Ridge and Ordinary Least Squares Estimators [PDF]
مجلة جامعة الانبار للعلوم الصرفةIn the presence of high correlation between the independent variables in the linear regression model, which is known as the multicollinearity problem, the ordinary least squares estimator produce large variations in the sample.
Karam Al-janabi, Mustafa Alheety
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A New Mixed Biased Estimator for Ill‐Conditioning Challenges in Linear Regression Model With Chemometrics Applications [PDF]
Analytical Science AdvancesIn linear regression models, the ordinary least squares (OLS) method is used to estimate the unknown regression coefficients. However, the OLS estimator may provide unreliable estimates in non‐orthogonal models.
Muhammad Amin +3 more
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Ordinary least squares estimation of a dynamic game model [PDF]
International Economic Review, 2016 Estimation of dynamic games is known to be a numerically challenging task. A common form of the payoff functions employed in practice takes the linear-in-parameter specification.
Srisuma, Sorawoot +8 more
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Temporal Aggregation and Ordinary Least Squares Estimation of Cointegrating Regressions [PDF]
, 2000 The paper derives the asymptotic distribution of the ordinary least squares estimator of cointegrating vectors with temporally aggregated time series.
Gabriel Pons Rotger
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On the Inconsistency of the Ordinary Least Squares Estimator for Spatial Autoregressive Processes [PDF]
, 2000 This paper investigates the asymptotic properties of the ordinary least squares estimator for spatial autoregressive models. We show that this estimator is biased as well as inconsistent for the parameters regardless of the distribution of the error term.
Théophile AZOMAHOU, Agénor LAHATTE
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Using Machine Learning to Improve Control for Confounding in the Dynamic Weighted Ordinary Least Squares Estimator of Optimal Adaptive Treatment Strategies [PDF]
Biometrical JournalMiceline Mesidor +2 more
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Statistics & Probability Letters, 2017 For seemingly unrelated regression (SUR) models with integrated regressors, two sufficient conditions are identified, under which the ordinary least-squares estimator (OLSE) is asymptotically efficient. The first condition is that every pair of regressor
신동완
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A new biased regression estimator: Theory, simulation and application
Scientific African, 2022 The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud +2 more
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Inference in Linear Models with Nonstochastic Biased Factors [PDF]
The Egyptian Statistical Journal, 1996 Obenchain (1977) claimed that ridge techniques with nonstochastic of biased factors don't generally yield "new" normal theory statistical inference than that used in least squares technique, and that the t and F statistics are identical under both ...
Abdul-Mordy Azzam
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