Results 31 to 40 of about 163,142 (181)
Modified One-Parameter Liu Estimator for the Linear Regression Model
Modelling and Simulation in Engineering, 2020 Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the multicollinearity problem for the linear regression model.
Adewale F. Lukman +3 more
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Robust Liu-Type Estimator for SUR Model
Statistics, Optimization & Information Computing, 2021 The Liu-type estimator is one of the shrink estimators that is used to remedy for a problem of multicollinearityin SUR model, but it is sensitive to the outlier. In this paper, we introduce the S Liu-type (SLiu-type) and MM Liu-type estimator (MMLiu-type) for SUR model.
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IEEE Access, 2021 A situation in which an image is combined with multiple images to form interferometric pairs is often observed in small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) deformation inversion, and this situation leads to a near linear
Min Zhai +6 more
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Mathematics, 2023 Following the idea presented with regard to the elastic-net and Liu-LASSO estimators, we proposed a new penalized estimator based on the Kibria–Lukman estimator with L1-norms to perform both regularization and variable selection.
Adewale Folaranmi Lukman +5 more
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Adaptive covariance matrix estimation through block thresholding [PDF]
, 2012 Estimation of large covariance matrices has drawn considerable recent attention, and the theoretical focus so far has mainly been on developing a minimax theory over a fixed parameter space.
Cai, T. Tony, Yuan, Ming
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A new Poisson Liu Regression Estimator: method and application [PDF]
Journal of Applied Statistics, 2019 This paper considers the estimation of parameters for the Poisson regression model in the presence of high, but imperfect multicollinearity. To mitigate this problem, we suggest using the Poisson Liu Regression Estimator (PLRE) and propose some new approaches to estimate this shrinkage parameter.
Muhammad Qasim +3 more
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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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Liu Estimates and Influence Analysis in Regression Models with Stochastic Linear Restrictions and AR (1) Errors [PDF]
Journal of Sciences, Islamic Republic of Iran, 2019 In the linear regression models with AR (1) error structure when collinearity exists, stochastic linear restrictions or modifications of biased estimators (including Liu estimators) can be used to reduce the estimated variance of the regression ...
Hoda Mohammadi, Abdolrahman Rasekh
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Axioms, 2023 The beta regression model (BRM) is used when the dependent variable may take continuous values and be bounded in the interval (0, 1), such as rates, proportions, percentages and fractions.
Muhammad Amin +3 more
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Lookahead Strategies for Sequential Monte Carlo [PDF]
, 2013 Based on the principles of importance sampling and resampling, sequential Monte Carlo (SMC) encompasses a large set of powerful techniques dealing with complex stochastic dynamic systems.
Chen, Rong, Lin, Ming, Liu, Jun S.
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