Results 11 to 20 of about 56,202 (281)
Multilocus association mapping using generalized ridge logistic regression [PDF]
BMC Bioinformatics, 2011 Background In genome-wide association studies, it is widely accepted that multilocus methods are more powerful than testing single-nucleotide polymorphisms (SNPs) one at a time.
Ott Jurg, Shen Yuanyuan, Liu Zhe
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PENERAPAN METODE GENERALIZED RIDGE REGRESSION DALAM MENGATASI MASALAH MULTIKOLINEARITAS
E-Jurnal Matematika, 2013 Ordinary least square is parameter estimation method for linier regression analysis by minimizing residual sum of square. In the presence of multicollinearity, estimators which are unbiased and have a minimum variance can not be generated ...
NI KETUT TRI UTAMI, I KOMANG GDE SUKARSA
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A novel generalized ridge regression method for quantitative genetics. [PDF]
Genetics, 2013 AbstractAs the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithm for situations in which the number of parameters largely exceeds the number of ...
Shen X, Alam M, Fikse F, Rönnegård L.
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Kernel Ridge Regression for Generalized Graph Signal Processing
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 In generalized graph signal processing (GGSP), a function (an element from a separable Hilbert space) is associated with each vertex. To perform non-linear filtering and regression under the GGSP framework, we formulate an operator-valued kernel ridge regression (KRR) filtering approach.
Jian, Xingchao, Tay, Wee Peng
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Feasible Generalized Stein-Rule Restricted Ridge Regression Estimators [PDF]
Journal of Applied Mathematics, Statistics and Informatics, 2017 AbstractSeveral versions of the Stein-rule estimators of the coefficient vector in a linear regression model are proposed in the literature. In the present paper, we propose new feasible generalized Stein-rule restricted ridge regression estimators to examine multicollinearity and autocorrelation problems simultaneously for the general linear ...
Ozbay, N., Dawoud, I., Kaciranlar, S.
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Efficient Generalized Ridge Regression
Open Statistics, 2022 Abstract The original ridge estimator of the unknown p×1 vector of β-coefficients in a linear model used a single scalar, k, to determine a point on a shrinkage path of finite length that extends from the Ordinary Least Squares estimator, ^β 0, to the shrinkage terminus (usually ^β ≡ 0). Generalized ridge estimators use
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Generalized ridge estimators adapted in structural equation models
Acta Scientiarum: Technology, 2020 Multicollinearity is detected via regression models, where independent variables are strongly correlated. Since they entail linear relations between observed or latent variables, the structural equation models (SEM) are subject to the multicollinearity ...
Gislene Araujo Pereira +2 more
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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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KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS
E-Jurnal Matematika, 2014 Ordinary least square is a parameter estimations for minimizing residual sum of squares. If the multicollinearity was found in the data, unbias estimator with minimum variance could not be reached.
HANY DEVITA +2 more
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Improving generalized ridge estimator for the gamma regression model. [PDF]
المجلة العراقية للعلوم الاحصائيةIt has been consistently proven that the ridge estimator is an effective shrinking strategy for reducing the effects of multicollinearity. An effective model to use when the response variable is positively skewed is the Gamma Regression Model (GRM ...
AVAN Al-Saffar, Zakaria Y. Algamal
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