Slope heuristics and V-Fold model selection in heteroscedastic regression using strongly localized bases [PDF]
, 2016 We investigate the optimality for model selection of the so-called slope heuristics, $V$-fold cross-validation and $V$-fold penalization in a heteroscedastic with random design regression context.
Navarro, Fabien, Saumard, Adrien
core +4 more sources
Bayesian Regularized SEM: Current Capabilities and Constraints
Psych, 2023 An important challenge in statistical modeling is to balance how well our model explains the phenomenon under investigation with the parsimony of this explanation.
Sara van Erp
doaj +1 more source
lassopack: Model selection and prediction with regularized regression in Stata [PDF]
, 2019 This article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso, square-root lasso, elastic net, ridge regression, adaptive lasso and post-estimation OLS.
Athey S. +6 more
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Bias reduction in the logistic model parameters with the LogF(1,1) penalty under MAR assumption
Frontiers in Applied Mathematics and Statistics, 2022 In this paper, we present a novel validated penalization method for bias reduction to estimate parameters for the logistic model when data are missing at random (MAR).
Muna Al-Shaaibi +3 more
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Boosting Correlation Based Penalization in Generalized Linear Models [PDF]
, 2007 In high dimensional regression problems penalization techniques are a useful tool for estimation and variable selection. We propose a novel penalization technique that aims at the grouping effect which encourages strongly correlated predictors to be in ...
Tutz, Gerhard, Ulbricht, Jan
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Application of Robust Statistics to Asset Allocation Models
Revstat Statistical Journal, 2007 Many strategies for asset allocation involve the computation of the expected value and the covariance matrix of the returns of financial instruments.
Roy E. Welsch , Xinfeng Zhou
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Accounting for the Role of Long Walks on Networks via a New Matrix Function [PDF]
, 2016 We introduce a new matrix function for studying graphs and real-world networks based on a double-factorial penalization of walks between nodes in a graph. This new matrix function is based on the matrix error function.
Estrada, Ernesto, Silver, Grant
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Refractory reverse amblyopia with atropine penalization
Oman Journal of Ophthalmology, 2010 Pharmacological penalization with atropine has been shown to be equally effective as conventional occlusion therapy in the treatment of amblyopia in children.
Preeti Ajit Patil +2 more
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Springer: An R package for bi-level variable selection of high-dimensional longitudinal data
Frontiers in Genetics, 2023 In high-dimensional data analysis, the bi-level (or the sparse group) variable selection can simultaneously conduct penalization on the group level and within groups, which has been developed for continuous, binary, and survival responses in the ...
Fei Zhou +4 more
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Adaptive wavelet simulation of global ocean dynamics using a new Brinkman volume penalization [PDF]
Geoscientific Model Development, 2015 In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations.
N. K.-R. Kevlahan, T. Dubos, M. Aechtner
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