Results 51 to 60 of about 163,142 (181)
AIP AdvancesCount data often exhibit dispersion patterns that the standard Poisson regression model struggles to handle, particularly in cases of overdispersion or underdispersion. The generalized Poisson regression model (GPRM) provides a more flexible alternative,
Ali T. Hammad +3 more
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On estimation of the diagonal elements of a sparse precision matrix
, 2016 In this paper, we present several estimators of the diagonal elements of the inverse of the covariance matrix, called precision matrix, of a sample of iid random vectors. The focus is on high dimensional vectors having a sparse precision matrix.
Balmand, Samuel, Dalalyan, Arnak S.
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Robust PC with wild bootstrap estimation of linear model in the presence of outliers, multicollinearity and heteroscedasticity error variance [PDF]
, 2015 The regression model estimator is considered efficient if it is robust and resistant to the presence of heteroscedasticity variance, multicollinearity or unusual observations called outliers.
Adnan, Robiah +3 more
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Capacity-Achieving Iterative LMMSE Detection for MIMO-NOMA Systems
, 2016 This paper considers a iterative Linear Minimum Mean Square Error (LMMSE) detection for the uplink Multiuser Multiple-Input and Multiple-Output (MU-MIMO) systems with Non-Orthogonal Multiple Access (NOMA).
Guan, Yong Liang +3 more
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A New Liu Type of Estimator for the Restricted SUR Estimator
Journal of Modern Applied Statistical Methods, 2020 A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived.
Kristofer Månsson +2 more
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User-Friendly Covariance Estimation for Heavy-Tailed Distributions [PDF]
, 2019 We offer a survey of recent results on covariance estimation for heavy-tailed distributions. By unifying ideas scattered in the literature, we propose user-friendly methods that facilitate practical implementation. Specifically, we introduce element-wise
Ke, Yuan +4 more
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New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model
مجلة بغداد للعلوم, 2020 This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model.
Mustafa Ismaeel Naif Alheety
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The Generalized Spectral Kurtosis Estimator
, 2010 Due to its conceptual simplicity and its proven effectiveness in real-time detection and removal of radio frequency interference (RFI) from radio astronomy data, the Spectral Kurtosis (SK) estimator is likely to become a standard tool of a new generation
D. E. Gary +8 more
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High Dimensional Semiparametric Gaussian Copula Graphical Models
, 2012 In this paper, we propose a semiparametric approach, named nonparanormal skeptic, for efficiently and robustly estimating high dimensional undirected graphical models.
Han, Fang +4 more
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Improved Liu Estimator for the Beta Regression Model: Methods, Simulation and Applications [PDF]
Operations Research and DecisionsThe beta regression model (BRM) is a well-known approach to modeling a response variable that has a beta distribution. The maximum likelihood estimator (MLE) does not produce accurate results for the BRM when there is a high degree of multicollinearity ...
Nimra Ilyas +3 more
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