Pages that link to "Item:Q619141"

The following pages link to \(\ell_{1}\)-penalization for mixture regression models (Q619141):

Displaying 50 items.

• Joint rank and variable selection for parsimonious estimation in a high-dimensional finite mixture regression model (Q2397123) (← links)
• Model-based regression clustering for high-dimensional data: application to functional data (Q2418303) (← links)
• Penalized estimation in high-dimensional hidden Markov models with state-specific graphical models (Q2441854) (← links)
• Endogeneity in high dimensions (Q2510821) (← links)
• Maximin effects in inhomogeneous large-scale data (Q2515497) (← links)
• Penalised robust estimators for sparse and high-dimensional linear models (Q2664993) (← links)
• Covariance matrix estimation of the maximum likelihood estimator in multivariate clusterwise linear regression (Q2665004) (← links)
• Modeling cell populations measured by flow cytometry with covariates using sparse mixture of regressions (Q2686038) (← links)
• An \(\ell_1\)-oracle inequality for the Lasso in multivariate finite mixture of multivariate Gaussian regression models (Q2786498) (← links)
• Regularization in finite mixture of regression models with diverging number of parameters (Q2846451) (← links)
• Estimation for high-dimensional linear mixed-effects models using \(\ell_1\)-penalization (Q2911662) (← links)
• Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models (Q3016190) (← links)
• A hierarchical Bayesian perspective on majorization-minimization for non-convex sparse regression: application to M/EEG source imaging (Q4571033) (← links)
• Adapting to unknown noise level in sparse deconvolution (Q4603711) (← links)
• A Sparse Learning Approach to Relative-Volatility-Managed Portfolio Selection (Q4988547) (← links)
• Penalized proportion estimation for non parametric mixture of regressions (Q5077371) (← links)
• A new model selection procedure for finite mixture regression models (Q5077504) (← links)
• A robust high dimensional estimation of a finite mixture of the generalized linear model (Q5092682) (← links)
• Penalized estimation in finite mixture of ultra-high dimensional regression models (Q5095987) (← links)
• Bayesian variable selection in a finite mixture of linear mixed-effects models (Q5107465) (← links)
• A New Semiparametric Approach to Finite Mixture of Regressions using Penalized Regression via Fusion (Q5109919) (← links)
• Variable selection approach for zero-inflated count data via adaptive lasso (Q5128631) (← links)
• Model selection in finite mixture of regression models: a Bayesian approach with innovative weighted<i>g</i>priors and reversible jump Markov chain Monte Carlo implementation (Q5220880) (← links)
• Screening and clustering of sparse regressions with finite non‐Gaussian mixtures (Q5283309) (← links)
• Mixtures, Envelopes and Hierarchical Duality (Q5378366) (← links)
• Identification of sparse FIR systems using a general quantisation scheme (Q5494503) (← links)
• Quasi-likelihood and/or robust estimation in high dimensions (Q5965304) (← links)
• High-dimensional regression with unknown variance (Q5965306) (← links)
• A general theory of concave regularization for high-dimensional sparse estimation problems (Q5965310) (← links)
• Comments on: ``A random forest guided tour'' (Q5972095) (← links)
• Histopathological imaging‐based cancer heterogeneity analysis via penalized fusion with model averaging (Q6055496) (← links)
• Hierarchical cancer heterogeneity analysis based on histopathological imaging features (Q6055707) (← links)
• Variance estimation in high-dimensional linear regression via adaptive elastic-net (Q6065189) (← links)
• A Critical Review of LASSO and Its Derivatives for Variable Selection Under Dependence Among Covariates (Q6067162) (← links)
• Regression‐based heterogeneity analysis to identify overlapping subgroup structure in high‐dimensional data (Q6068650) (← links)
• Regularization in dynamic random‐intercepts models for analysis of longitudinal data (Q6073414) (← links)
• Heterogeneity Analysis via Integrating Multi-Sources High-Dimensional Data With Applications to Cancer Studies (Q6086163) (← links)
• Modelling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures (Q6086487) (← links)
• Mixture of inhomogeneous matrix models for species‐rich ecosystems (Q6139123) (← links)
• Estimation of multiple networks with common structures in heterogeneous subgroups (Q6536691) (← links)
• Functional mixtures-of-experts (Q6547772) (← links)
• Asymptotic bias of the \(\ell_2\)-regularized error variance estimator (Q6548541) (← links)
• Integrated subgroup identification from multi-source data (Q6561258) (← links)
• Challenges in model-based clustering (Q6562689) (← links)
• Clustering electricity consumers using high-dimensional regression mixture models (Q6576828) (← links)
• Sparse estimation in semiparametric finite mixture of varying coefficient regression models (Q6589289) (← links)
• Aggregated inference (Q6600359) (← links)
• Information-incorporated sparse hierarchical cancer heterogeneity analysis (Q6618514) (← links)
• Image-Based Prognostics Using Penalized Tensor Regression (Q6621649) (← links)
• Mixture of Regression Models for Large Spatial Datasets (Q6621664) (← links)