Results 21 to 30 of about 354,947 (289)
On Knots locations for Regression Spline Estimator [PDF]
المجلة العراقية للعلوم الاحصائية, 2013 Regression splines is one of the methods that are used to estimate the regression curve non parametrically. One of the most important elements that contribute to the application of the method is to determine the degree of the spline function and the ...
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Regression Estimator Using Double Ranked Set Sampling
Sultan Qaboos University Journal for Science, 2002 The performance of a regression estimator based on the double ranked set sample (DRSS) scheme, introduced by Al-Saleh and Al-Kadiri (2000), is investigated when the mean of the auxiliary variable X is unknown.
Hani M. Samawi, Eman M. Tawalbeh
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M-estimators for isotonic regression [PDF]
Journal of Statistical Planning and Inference, 2012 In this paper we propose a family of robust estimates for isotonic regression: isotonic M-estimators. We show that their asymptotic distribution is, up to an scalar factor, the same as that of Brunk's classical isotonic estimator. We also derive the influence function and the breakdown point of these estimates.
Alvarez, Enrique Ernesto +1 more
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Handling Nonresponse in Business Surveys
Survey Research Methods, 2012 Business surveys are a valuable indication of the current and the future economic situation. However refusals are very common in this context and may induce bias in the estimates of interest.
Riccardo Borgoni +2 more
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Improved Mixed Estimator Using Two Auxiliary Variables For Full Extreme Maximum And Minimum Values In Single Phase Sampling [PDF]
المجلة العراقية للعلوم الاحصائيةThe use of multiple auxiliary variables has been established to improve precision in the estimators of ratio, regression and product respectively. However, the presence of extreme values in the distribution could annul such efficiency Olatayo et al ...
Timothy O. Olatayo +2 more
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A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model
Stats, 2020 In a multiple linear regression model, the ordinary least squares estimator is inefficient when the multicollinearity problem exists. Many authors have proposed different estimators to overcome the multicollinearity problem for linear regression models ...
Issam Dawoud, B. M. Golam Kibria
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Model-robust regression and a Bayesian ``sandwich'' estimator [PDF]
, 2010 We present a new Bayesian approach to model-robust linear regression that leads to uncertainty estimates with the same robustness properties as the Huber--White sandwich estimator.
Lumley, Thomas +2 more
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Robust weighted ridge regression based on S – estimator
African Scientific Reports, 2023 Ordinary least squares (OLS) estimator performance is seriously threatened by correlated regressors often called multicollinearity. Multicollinearity is a situation when there is strong relationship between any two exogenous variables.
Taiwo Stephen Fayose +3 more
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F1000Research, 2021 Background: In the linear regression model, the ordinary least square (OLS) estimator performance drops when multicollinearity is present. According to the Gauss-Markov theorem, the estimator remains unbiased when there is multicollinearity, but the ...
BENEDICTA Aladeitan +4 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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