Results 21 to 30 of about 825 (114)
The distribution of model averaging estimators and an impossibility result regarding its estimation [PDF]
, 2006 The finite-sample as well as the asymptotic distribution of Leung and Barron's (2006) model averaging estimator are derived in the context of a linear regression model. An impossibility result regarding the estimation of the finite-sample distribution of
Benedikt M. Pötscher +1 more
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On the adaptive elastic-net with a diverging number of parameters [PDF]
, 2009 We consider the problem of model selection and estimation in situations where the number of parameters diverges with the sample size. When the dimension is high, an ideal method should have the oracle property [J. Amer. Statist. Assoc.
Zhang, Hao Helen, Zou, Hui
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Some remarks on a pair of seemingly unrelated regression models
Open Mathematics, 2019 Linear regression models are foundation of current statistical theory and have been a prominent object of study in statistical data analysis and inference.
Hou Jian, Zhao Yong
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Optimally bounding a generalized gross error sensitivity of unbounded influence M-estimates of regression [PDF]
, 1992 This paper presents an approximation for assessing the effect of deleting an observation in the eigenvalues of the correlation matrix of a multiple linear regression modelo Applications in connection with the detection of collinearityinfluential ...
Yohai, Víctor J., Zamar, Rubén
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Sparse Conformal Predictors [PDF]
, 2009 Conformal predictors, introduced by Vovk et al. (2005), serve to build prediction intervals by exploiting a notion of conformity of the new data point with previously observed data.
Hebiri, Mohamed
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Statistical estimation in the proportional hazards model with risk set sampling [PDF]
, 2004 Thomas' partial likelihood estimator of regression parameters is widely used in the analysis of nested case-control data with Cox's model. This paper proposes a new estimator of the regression parameters, which is consistent and asymptotically normal ...
Chen, Kani
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Parameter Estimation of the Partially Linear Quantile Regression Model Under Monotonic Constraints
Journal of Mathematics, Volume 2025, Issue 1, 2025.The paper brings forward the partially linear quantile regression model by incorporating monotonic constraints, which are common in real‐world relationships between variables. It introduces two novel parameter estimation methods, that is, the coordinate descent method and the profile likelihood method, which eliminate the extensive tuning and simplify ...
Shujin Wu +4 more
wiley +1 more source
Selection of tuning parameters in bridge regression models via Bayesian information criterion
, 2012 We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge
A Antoniadis +29 more
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e-Prime: Advances in Electrical Engineering, Electronics and EnergyThis study investigates the performance of solar cell electric power generation, focusing on data collected from Prince of Songkla University, Surat Thani Campus, analyzing the Mean Squared Error (MSE) for each phase consisting of Phase A: 0.00133, Phase
Nathaphon Boonnam, Orachon Lanteng
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Demonstratio MathematicaSuppose that a weakly singular linear regression model M{\mathscr{M}} and its two competing restricted models M1{{\mathscr{M}}}_{1} and M2{{\mathscr{M}}}_{2} are given.
Ren Xingwei
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