Pages that link to "Item:Q147375"
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The following pages link to The Adaptive Lasso and Its Oracle Properties (Q147375):
Displaying 50 items.
- Fully Bayes factors with a generalized \(g\)-prior (Q661180) (← links)
- Near-optimal stochastic approximation for online principal component estimation (Q681490) (← links)
- Adaptive LASSO for general transformation models with right censored data (Q693274) (← links)
- Adaptive sequential design for regression on multi-resolution bases (Q693303) (← links)
- The predictive Lasso (Q693339) (← links)
- Nonconcave penalized composite conditional likelihood estimation of sparse Ising models (Q693730) (← links)
- Robust rank correlation based screening (Q693749) (← links)
- Order selection in nonlinear time series models with application to the study of cell memory (Q714378) (← links)
- Rank-based Liu regression (Q722749) (← links)
- Shrinkage estimation in linear mixed models for longitudinal data (Q723454) (← links)
- Group and within-group variable selection for competing risks data (Q725412) (← links)
- Sparse factor regression via penalized maximum likelihood estimation (Q725684) (← links)
- Quantile index coefficient model with variable selection (Q730423) (← links)
- Bayesian regularized quantile structural equation models (Q730442) (← links)
- Some theoretical results on the grouped variables Lasso (Q734551) (← links)
- Variable selection for semiparametric varying coefficient partially linear models (Q734698) (← links)
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization (Q734955) (← links)
- Variable selection for varying-coefficient models with the sparse regularization (Q736986) (← links)
- Sparse recovery via differential inclusions (Q739470) (← links)
- Regularized rank-based estimation of high-dimensional nonparanormal graphical models (Q741796) (← links)
- Bayesian adaptive Lasso (Q743993) (← links)
- Variable selection in high-dimensional double generalized linear models (Q744756) (← links)
- Model selection by LASSO methods in a change-point model (Q744757) (← links)
- Variational approximation for heteroscedastic linear models and matching pursuit algorithms (Q746230) (← links)
- On Bayesian lasso variable selection and the specification of the shrinkage parameter (Q746286) (← links)
- A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems (Q746299) (← links)
- Random effects selection in generalized linear mixed models via shrinkage penalty function (Q746316) (← links)
- Shrinkage estimation of varying covariate effects based on quantile regression (Q746335) (← links)
- Multi-species distribution modeling using penalized mixture of regressions (Q746675) (← links)
- Sample size determination for training cancer classifiers from microarray and RNA-seq data (Q746699) (← links)
- Wavelet-domain regression and predictive inference in psychiatric neuroimaging (Q746704) (← links)
- Quantile regression for dynamic partially linear varying coefficient time series models (Q746867) (← links)
- Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models (Q746868) (← links)
- LASSO-based multivariate linear profile monitoring (Q763195) (← links)
- Variable selection using penalized empirical likelihood (Q763671) (← links)
- Sparse estimation in functional linear regression (Q764470) (← links)
- Principled sure independence screening for Cox models with ultra-high-dimensional covariates (Q764508) (← links)
- Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data (Q764510) (← links)
- An easy-to-implement hierarchical standardization for variable selection under strong heredity constraint (Q777839) (← links)
- Efficient parameter estimation and variable selection in partial linear varying coefficient quantile regression model with longitudinal data (Q779677) (← links)
- Variable selection for spatial autoregressive models with a diverging number of parameters (Q779691) (← links)
- Conditional distance correlation screening for sparse ultrahigh-dimensional models (Q821654) (← links)
- Adaptive and reversed penalty for analysis of high-dimensional correlated data (Q823261) (← links)
- Single- and multiple-group penalized factor analysis: a trust-region algorithm approach with integrated automatic multiple tuning parameter selection (Q823858) (← links)
- MM algorithms for distance covariance based sufficient dimension reduction and sufficient variable selection (Q829724) (← links)
- Robust variable selection with exponential squared loss for the spatial autoregressive model (Q829731) (← links)
- Variable selection in high-dimensional linear model with possibly asymmetric errors (Q829750) (← links)
- Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection (Q830063) (← links)
- Variable selection in finite mixture of regression models with an unknown number of components (Q830075) (← links)
- Censored mean variance sure independence screening for ultrahigh dimensional survival data (Q830110) (← links)
