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Nonlinear Shrinkage Estimation of Higher-Order Moments for Portfolio Optimization Under Uncertainty in Complex Financial Systems [PDF]
EntropyThis paper develops a nonlinear shrinkage estimation method for higher-order moment matrices within a multifactor model framework and establishes its asymptotic consistency under high-dimensional settings.
Wanbo Lu, Zhenzhong Tian
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Efficient Post-Shrinkage Estimation Strategies in High-Dimensional Cox’s Proportional Hazards Models [PDF]
EntropyRegularization methods such as LASSO, adaptive LASSO, Elastic-Net, and SCAD are widely employed for variable selection in statistical modeling. However, these methods primarily focus on variables with strong effects while often overlooking weaker signals,
Syed Ejaz Ahmed +2 more
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Shrinkage estimation of non-negative mean vector with unknown covariance under balance loss [PDF]
Journal of Inequalities and Applications, 2018 Parameter estimation in multivariate analysis is important, particularly when parameter space is restricted. Among different methods, the shrinkage estimation is of interest.
Hamid Karamikabir +2 more
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Estimation of a Parallel Stress-strength Model Based on the Inverse Kumaraswamy Distribution
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2023 The reliability of the stress-strength model attracted many statisticians for several years owing to its applicability in different and diverse parts such as engineering, quality control, and economics. In this paper, the system reliability estimation in
Bayda A. Kalaf +3 more
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Axioms, 2021 Meta-analyses combine the estimators of individual means to estimate the common mean of a population. However, the common mean could be undefined or uninformative in some scenarios where individual means are “ordered” or “sparse”.
Nanami Taketomi +3 more
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Linear Shrinkage and Shrinkage Pretest Strategies in Partially Linear Models [PDF]
E3S Web of Conferences, 2023 In this paper, we improved the efficiency of parameter estimation in partially linear models, where subspace information is available. We proposed linear shrinkage and shrinkage pretest estimation strategies.
Phukongtong Siwaporn +2 more
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Applied Sciences, 2022 A covariance matrix is an important parameter in many computational applications, such as quantitative trading. Recently, a global minimum variance portfolio received great attention due to its performance after the 2007–2008 financial crisis, and this ...
Tuan Tran, Nhat Nguyen, Trung Nguyen
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Shrinking the Variance in Experts’ “Classical” Weights Used in Expert Judgment Aggregation
Forecasting, 2023 Mathematical aggregation of probabilistic expert judgments often involves weighted linear combinations of experts’ elicited probability distributions of uncertain quantities. Experts’ weights are commonly derived from calibration experiments based on the
Gayan Dharmarathne +3 more
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Ordinary and Bayesian Shrinkage Estimation [PDF]
مجلة جامعة النجاح للأبحاث العلوم الطبيعية, 2007 In this paper a variety of shrinkage methods for estimating unknown population parameters has been considered. Aprior distribution for the parameters around their natural origins has been postulated and the ordinary Bayes estimators are used in place of ...
Mohammad Qabaha
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meta.shrinkage: An R Package for Meta-Analyses for Simultaneously Estimating Individual Means
Algorithms, 2022 Meta-analysis is an indispensable tool for synthesizing statistical results obtained from individual studies. Recently, non-Bayesian estimators for individual means were proposed by applying three methods: the James–Stein (JS) shrinkage estimator ...
Nanami Taketomi +3 more
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