Results 1 to 10 of about 2,713,196 (185)
Modified Unbiased Optimal Estimator For Linear Regression Model [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2023 In this paper, we propose a novel form of Generalized Unbiased Optimal Estimator where the explanatory variables are multicollinear. The proposed estimator's bias, variance, and mean square error matrix (MSE) are calculated.
Hussein AL-jumaili, Mustafa Alheety
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Bayesian linear regression model for method comparison studies
Ceylon Journal of Science, 2022 Method comparison is an essential area related to clinical science and study to compare a new method with an existing method to check if a new one can replace with an existing method.
S.M.M. Lakmali +2 more
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Robust Model Selection in Linear regression [PDF]
Kirkuk Journal of Science, 2007 The research deals with the proposing of robust formula for the accumulate prediction error (APE) criterion which is used in selecting regression model. The proposed formula evaluated with a simulation study.
Dr. Sabah Haseeb Hassan
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A mixture of linear-linear regression models for a linear-circular regression [PDF]
Statistical Modelling, 2019 We introduce a new approach to a linear-circular regression problem that relates multiple linear predictors to a circular response. We follow a modelling approach of a wrapped normal distribution that describes angular variables and angular distributions and advances them for a linear-circular regression analysis.
Sikaroudi, Ali Esmaieeli, Park, Chiwoo
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Robust Functional Linear Regression Models
The R Journal, 2023 With advancements in technology and data storage, the availability of functional data whose sample observations are recorded over a continuum, such as time, wavelength, space grids, and depth, progressively increases in almost all scientific branches. The functional linear regression models, including scalar-on-function and function-on-function, have ...
Ufuk Beyaztas, Han Lin Shang
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Kuwait Journal of Science, 2023 Ridge regression is employed to estimate the regression parameters while circumventing the multicollinearity among independent variables. The ridge parameter plays a vital role as it controls bias-variance tradeoff. Several methods for choosing the ridge
Irum Sajjad Dar +3 more
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Linear regression for uplift modeling [PDF]
Data Mining and Knowledge Discovery, 2018 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Krzysztof Rudas, Szymon Jaroszewicz
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A New Regression Model: Modal Linear Regression [PDF]
Scandinavian Journal of Statistics, 2013 ABSTRACTThe mode of a distribution provides an important summary of data and is often estimated on the basis of some non‐parametric kernel density estimator. This article develops a new data analysis tool called modal linear regression in order to explore high‐dimensional data. Modal linear regression models the conditional mode of a response Y given a
Yao, Weixin, Li, Longhai
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A Linear Regression Thermal Displacement Lathe Spindle Model
Energies, 2020 Thermal error is one of the main reasons for the loss of accuracy in lathe machining. In this study, a thermal deformation compensation model is presented that can reduce the influence of spindle thermal error on machining accuracy.
Chih-Jer Lin +5 more
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Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model
The Scientific World Journal, 2020 The general linear regression model has been one of the most frequently used models over the years, with the ordinary least squares estimator (OLS) used to estimate its parameter.
Adewale F. Lukman +3 more
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