The following pages link to glmnet (Q20169):
Displaying 50 items.
- Performance Assessment of High-dimensional Variable Identification (Q5066768) (← links)
- A proximal dual semismooth Newton method for zero-norm penalized quantile regression estimator (Q5066792) (← links)
- Hypothesis Testing in High-Dimensional Instrumental Variables Regression With an Application to Genomics Data (Q5067438) (← links)
- A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer (Q5072590) (← links)
- Estimation of Sobol's sensitivity indices under generalized linear models (Q5075552) (← links)
- An improved comorbidity summary score for measuring disease burden and predicting mortality with applications to two national cohorts (Q5076926) (← links)
- Overlapping group lasso for high-dimensional generalized linear models (Q5076945) (← links)
- A new model selection procedure for finite mixture regression models (Q5077504) (← links)
- Optimal regression parameter-specific shrinkage by plug-in estimation (Q5077520) (← links)
- Rates of convergence of the adaptive elastic net and the post-selection procedure in ultra-high dimensional sparse models (Q5079021) (← links)
- Pliable lasso for the multinomial logistic regression (Q5079920) (← links)
- A new correction approach for information criteria to detect outliers in regression modeling (Q5079953) (← links)
- A modified information criterion for model selection (Q5079975) (← links)
- Performances of some high dimensional regression methods (Q5082657) (← links)
- Ensemble of penalized logistic models for classification of high-dimensional data (Q5082679) (← links)
- Diverse classifiers ensemble based on GMDH-type neural network algorithm for binary classification (Q5082990) (← links)
- Estimation and Selection for High-Order Markov Chains with Bayesian Mixture Transition Distribution Models (Q5083359) (← links)
- Adaptive Bayesian SLOPE: Model Selection With Incomplete Data (Q5083360) (← links)
- Penalized log-density estimation using Legendre polynomials (Q5083902) (← links)
- A modified multinomial baseline logit model with logit functions having different covariates (Q5083903) (← links)
- Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics (Q5083965) (← links)
- Comparing different propensity score estimation methods for estimating the marginal causal effect through standardization to propensity scores (Q5084764) (← links)
- Marginal maximum likelihood estimation methods for the tuning parameters of ridge, power ridge, and generalized ridge regression (Q5084943) (← links)
- Variable selection for semiparametric random-effects conditional density models with longitudinal data (Q5085624) (← links)
- Sparse group lasso for multiclass functional logistic regression models (Q5085971) (← links)
- Robust variable selection based on the random quantile LASSO (Q5086334) (← links)
- Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models (Q5086341) (← links)
- Goodness-of-fit Testing in High Dimensional Generalized Linear Models (Q5087155) (← links)
- Asymmetric influence measure for high dimensional regression (Q5093730) (← links)
- Variable selection in sparse GLARMA models (Q5095838) (← links)
- Penalized estimation in finite mixture of ultra-high dimensional regression models (Q5095987) (← links)
- Outlier-resistant high-dimensional regression modelling based on distribution-free outlier detection and tuning parameter selection (Q5106888) (← links)
- GPU parameter tuning for tall and skinny dense linear least squares problems (Q5113719) (← links)
- Optimal Sparse Linear Prediction for Block-missing Multi-modality Data Without Imputation (Q5120677) (← links)
- Ordinal ridge regression with categorical predictors (Q5126934) (← links)
- Variable selection for varying dispersion beta regression model (Q5128562) (← links)
- Variable selection approach for zero-inflated count data via adaptive lasso (Q5128631) (← links)
- Sparse cluster analysis of large-scale discrete variables with application to single nucleotide polymorphism data (Q5128918) (← links)
- Non-sparse<i>ϵ</i>-insensitive support vector regression for outlier detection (Q5130288) (← links)
- Individualized Multilayer Tensor Learning With an Application in Imaging Analysis (Q5130626) (← links)
- Independently Interpretable Lasso for Generalized Linear Models (Q5131139) (← links)
- A memory-based method to select the number of relevant components in principal component analysis (Q5131521) (← links)
- Readouts for echo-state networks built using locally regularized orthogonal forward regression (Q5139036) (← links)
- A generalized additive model approach to time-to-event analysis (Q5142210) (← links)
- Nuclear penalized multinomial regression with an application to predicting at bat outcomes in baseball (Q5142215) (← links)
- Predicting matches in international football tournaments with random forests (Q5142218) (← links)
- Identifying dynamical time series model parameters from equilibrium samples, with application to gene regulatory networks (Q5142250) (← links)
- Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms (Q5144778) (← links)
- A Tuning-free Robust and Efficient Approach to High-dimensional Regression (Q5146020) (← links)
- A mathematical model for image saturation with an application to the restoration of solar images via adaptive sparse deconvolution (Q5148419) (← links)
