Results 31 to 40 of about 4,452 (291)
Ridge Estimation for Multinomial Logit Models with Symmetric Side Constraints [PDF]
, 2009 In multinomial logit models, the identifiability of parameter estimates is typically obtained by side constraints that specify one of the response categories as reference category.
Tutz, Gerhard, Zahid, Faisal Maqbool
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Ancestral State Estimation with Phylogenetic Ridge Regression
Evolutionary Biology, 2020 The inclusion of fossil phenotypes as ancestral character values at nodes in phylogenetic trees is known to increase both the power and reliability of phylogenetic comparative methods (PCMs) applications. We implemented the R function RRphylo as to integrate fossil phenotypic information as ancestral character values.
Silvia Castiglione +8 more
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New estimators in a partial linear model depending on an unbiased ridge regression estimator [PDF]
EPJ Web of ConferencesThis paper introduces two new estimators based on the philosophy of unbiased ridge regression estimation, where the parameters are part of a partial linear model suffering from multicollinearity.
Al-Khazraji Yousif A. +1 more
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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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A study of local linear ridge regression estimators [PDF]
, 2011 In the case of the random design nonparametric regression, to correct for the unbounded finite-sample variance of the local linear estimator (LLE), Seifert and Gasser (J. Amer. Statist. Assoc.
鄧文舜; Deng, Wen-shuenn; Chu, C.K.; Cheng, M.Y.
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A new Jackknifing ridge estimator for logistic regression model [PDF]
, 2022 The ridge regression model has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The logistic regression model is a well-known model in application when the response variable is binary data ...
Algamal, Zakariya Y, Hammood, Nawal
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Modified jackknife ridge estimator for the Conway-Maxwell-Poisson model
Scientific African, 2023 Recently, research papers have shown a strong interest in modeling count data. The over-dispersion or under-dispersion are frequently seen in the count data.
Zakariya Yahya Algamal +3 more
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Modified Ridge Estimator for Poisson Regression
Cumhuriyet Science JournalPoisson regression is a statistical model used to model the relationship between a count-valued-dependent variable and one or more independent variables. A frequently encountered problem when modeling such relationships is multicollinearity, which occurs
Shuaib Mursal Ibrahim, Aydın Karakoca
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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 hybrid estimator for linear regression model analysis: Computations and simulations
Scientific African, 2023 The Linear regression model explores the relationship between a response variable and one or more independent variables. The parameters in the model are often estimated using the Ordinary Least Square Estimator (OLSE).
G.A. Shewa, F.I. Ugwuowo
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