Results 51 to 60 of about 5,491 (290)
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
doaj +1 more source
BAYESIAN-RIDGE ESTIMATOR FOR LINEAR REGRESSION MODEL
, 2023 Multicollinearity is a problem associated with inter-dependence of explanatory variables in linear regression model. The inefficiency of the Ordinary Least Square (OLS) Estimator lead to development of various other methods which include the Ridge ...
Idowu Usman
core +1 more source
Research in StatisticsThis article proposes some new estimators, namely Stein’s estimators for ridge regression and Kibria and Lukman estimator and compares their performance with some existing estimators, namely maximum likelihood estimator (MLE), ridge regression estimator,
Md Ariful Hoque, B. M. Golam Kibria
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Ridge Regression and Generalized Maximum Entropy: An improved version of the Ridge–GME parameter estimator [PDF]
, 2017 In this article, the Ridge–GME parameter estimator, which combines Ridge Regression and Generalized Maximum Entropy, is improved in order to eliminate the subjectivity in the analysis of the ridge trace.
Pedro Macedo (3610070)
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An improved ridge type estimator for logistic regression
, 2022 In this paper, an improved ridge type estimator is introduced to overcome the effect of multicollinearity in logistic regression. The proposed estimator is called a modified almost unbiased ridge logistic estimator.
Varathan, Nagarajah
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Ibn Al-Haitham Journal for Pure and Applied Sciences, 2018 In the presence of multi-collinearity problem, the parameter estimation method based on the ordinary least squares procedure is unsatisfactory. In 1970, Hoerl and Kennard insert analternative method labeled as estimator of ridge regression.
Hazim Mansoor Gorgees +1 more
doaj +1 more source
M Robust Weighted Ridge Estimator in Linear Regression Model
African Scientific Reports, 2023 Correlated regressors are a major threat to the performance of the conventional ordinary least squares (OLS) estimator. The ridge estimator provides more stable estimates in this circumstance.
Taiwo Stephen Fayose +2 more
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Good and Optimal Ridge Estimators
The Annals of Statistics, 1978 In generalized ridge estimation, the components of the ordinary least squares (OLS) regression coefficient vector which lie along the principal axes of the given regressor data are rescaled using known ridge factors. Generalizing a result of Swindel and Chapman, it is shown that, if each ridge factor is nonstochastic, nonnegative, and less than one ...
openaire +3 more sources
FEBS Letters, EarlyView.Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley +1 more source
FEBS Open Bio, EarlyView.Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source