Large Covariance Estimation by Thresholding Principal Orthogonal Complements [PDF]
, 2013 This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-
Fan, Jianqing +2 more
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Applications of Some Improved Estimators in Linear Regression [PDF]
, 2005 The problem of estimation of the regression coefficients under multicollinearity situation for the restricted linear model is discussed. Some improve estimators are considered, including the unrestricted ridge regression estimator (URRE), restricted ...
Kibria, B. M. Golam
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A new class of Poisson Ridge-type estimator
Scientific Reports, 2023 The Poisson Regression Model (PRM) is one of the benchmark models when analyzing the count data. The Maximum Likelihood Estimator (MLE) is used to estimate the model parameters in PRMs. However, the MLE may suffer from various drawbacks that arise due to
Esra Ertan, Kadri Ulaş Akay
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K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model
Mathematics, 2023 Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and Lukman estimator (KLE) was developed as an alternative to the MLE to handle multicollinearity ...
Adewale F. Lukman +5 more
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A High-Dimensional Counterpart for the Ridge Estimator in Multicollinear Situations
Mathematics, 2021 The ridge regression estimator is a commonly used procedure to deal with multicollinear data. This paper proposes an estimation procedure for high-dimensional multicollinear data that can be alternatively used.
Mohammad Arashi +3 more
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Rethinking the Effective Sample Size [PDF]
, 2018 The effective sample size (ESS) is widely used in sample-based simulation methods for assessing the quality of a Monte Carlo approximation of a given distribution and of related integrals.
Elvira, Víctor +2 more
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Liu-Type logistic estimator under Stochastic Linear Restrictions
Ceylon Journal of Science, 2018 To conquer the multicollinearity problem in logistic regression, many alternative estimators have been proposed in the literature when some linear restrictions on the parameter space are available in addition to the sample model.
Nagarajah Varathan +1 more
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Some one and two parameter estimators for the multicollinear gaussian linear regression model: simulations and applications [PDF]
Surveys in Mathematics and its Applications, 2023 The ordinary least square estimator is inefficient when there exists multicollinearity among regressors in linear regression model. There are many methods available in literature to solve the multicollinearity problem. In this study, we consider some one
Md Ariful Hoque , B. M. Golam Kibria
doaj
A new almost unbiased estimator in stochastic linear restriction model [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 In this paper, a new almost unbiased estimator is proposed under stochastic linear restrictions model as alternative to mixed estimator. The performance of the proposed estimator compared to mixed estimator is examined using the matrix mean squared ...
Mustafa Ismaeel Naif
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Optimal computational and statistical rates of convergence for sparse nonconvex learning problems [PDF]
, 2013 We provide theoretical analysis of the statistical and computational properties of penalized $M$-estimators that can be formulated as the solution to a possibly nonconvex optimization problem.
Liu, Han, Wang, Zhaoran, Zhang, Tong
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