Results 11 to 20 of about 353,670 (291)
Risk Estimation via Regression [PDF]
Operations Research, 2015 We introduce a regression-based nested Monte Carlo simulation method for the estimation of financial risk. An outer simulation level is used to generate financial risk factors and an inner simulation level is used to price securities and compute portfolio losses given risk factor outcomes.
Broadie, Mark +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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F1000Research, 2021 Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear model. Alternative estimators to the MLE include the ridge estimator, the Liu estimator and the
Olukayode Adebimpe +4 more
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Mathematics, 2023 For nonparametric regression estimation, conventional research all focus on isotropic regression function. In this paper, a linear wavelet estimator of anisotropic regression function is constructed, the rate of convergence of this estimator is discussed
Jia Chen, Junke Kou
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Minimax Ridge Regression Estimation. [PDF]
The Annals of Statistics, 1977 The technique of ridge regression, first proposed by Hoerl and Kennard, has become a popular tool for data analysts faced with a high degree of multicollinearity in their data. By using a ridge estimator, one hopes to both stabilize one's estimates (lower the condition number of the design matrix) and improve upon the squared error loss of the least ...
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A new biased regression estimator: Theory, simulation and application
Scientific African, 2022 The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud +2 more
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Locally Adaptive Nonparametric Binary Regression [PDF]
, 2007 A nonparametric and locally adaptive Bayesian estimator is proposed for estimating a binary regression. Flexibility is obtained by modeling the binary regression as a mixture of probit regressions with the argument of each probit regression having a thin
Cottet, Remy +4 more
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Predictive Estimation of Population Mean in Ranked Set Sampling
Revstat Statistical Journal, 2019 The article presents predictive estimation of population mean of the study variable in Ranked Set Sampling (RSS). It is shown that the predictive estimators in RSS using mean per unit estimator, ratio estimator and regression estimator as predictor for ...
Shakeel Ahmed +2 more
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The shooting S-estimator for robust regression [PDF]
, 2015 To perform multiple regression, the least squares estimator is commonly used. However, this estimator is not robust to outliers. Therefore, robust methods such as S-estimation have been proposed.
Alfons, Andreas +2 more
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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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