Pages that link to "Item:Q1354430"
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The following pages link to Heuristics of instability and stabilization in model selection (Q1354430):
Displaying 50 items.
- Sparse estimation and inference for censored median regression (Q963882) (← links)
- A principal component analysis for trees (Q965130) (← links)
- Improving the precision of classification trees (Q965140) (← links)
- On sparse estimation for semiparametric linear transformation models (Q972891) (← links)
- A survey of cross-validation procedures for model selection (Q975579) (← links)
- Penalized variable selection procedure for Cox models with semiparametric relative risk (Q987999) (← links)
- Parsimonious additive models (Q1019916) (← links)
- Detecting an interaction between treatment and a continuous covariate: a comparison of two approaches (Q1020054) (← links)
- Input selection and shrinkage in multiresponse linear regression (Q1020828) (← links)
- Classification tree analysis using TARGET (Q1023462) (← links)
- Empirical characterization of random forest variable importance measures (Q1023556) (← links)
- On properties of predictors derived with a two-step bootstrap model averaging approach -- a simulation study in the linear regression model (Q1023609) (← links)
- Predictive performance of Dirichlet process shrinkage methods in linear regression (Q1023703) (← links)
- A nonlinear multi-dimensional variable selection method for high dimensional data: sparse MAVE (Q1023796) (← links)
- An improved model averaging scheme for logistic regression (Q1026355) (← links)
- Almost everywhere behavior of general wavelet shrinkage operators (Q1577562) (← links)
- Estimator selection and combination in scalar-on-function regression (Q1615246) (← links)
- Tuning parameter selection in sparse regression modeling (Q1621202) (← links)
- Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations (Q1621346) (← links)
- Expectile regression for analyzing heteroscedasticity in high dimension (Q1640971) (← links)
- Statistics for big data: a perspective (Q1642374) (← links)
- Variable selection and parameter estimation with the Atan regularization method (Q1658121) (← links)
- Robust group identification and variable selection in regression (Q1658186) (← links)
- A multi-row deletion diagnostic for influential observations in small-sample regressions (Q1658468) (← links)
- Moderately clipped Lasso (Q1663146) (← links)
- High-dimensional simultaneous inference with the bootstrap (Q1694480) (← links)
- A penalized likelihood method for structural equation modeling (Q1695631) (← links)
- Variable selection and estimation using a continuous approximation to the \(L_0\) penalty (Q1695760) (← links)
- Assessing variable importance in clustering: a new method based on unsupervised binary decision trees (Q1729346) (← links)
- Forecasting with temporal hierarchies (Q1754013) (← links)
- Competitiveness of nations: a knowledge discovery examination (Q1779548) (← links)
- Nonparametric bootstrap prediction (Q1781189) (← links)
- High-dimensional inference: confidence intervals, \(p\)-values and R-software \texttt{hdi} (Q1790302) (← links)
- Broken adaptive ridge regression and its asymptotic properties (Q1795597) (← links)
- Robust variable selection through MAVE (Q1800060) (← links)
- Arcing classifiers. (With discussion) (Q1807115) (← links)
- Variable selection for Cox's proportional hazards model and frailty model (Q1848930) (← links)
- Analyzing bagging (Q1848962) (← links)
- Nonconcave penalized likelihood with a diverging number of parameters. (Q1879926) (← links)
- Generalization bounds for averaged classifiers (Q1879971) (← links)
- Evaluating the impact of exploratory procedures in regression prediction: A pseudosample approach (Q1896164) (← links)
- Partial linear single index models with distortion measurement errors (Q1934488) (← links)
- LAD variable selection for linear models with randomly censored data (Q1936296) (← links)
- Sharp oracle inequalities for aggregation of affine estimators (Q1940775) (← links)
- Penalized orthogonal-components regression for large \(p\) small \(n\) data (Q1952001) (← links)
- Composite kernel learning (Q1959567) (← links)
- A cubic spline penalty for sparse approximation under tight frame balanced model (Q1986544) (← links)
- Statistical inference for linear regression models with additive distortion measurement errors (Q2029215) (← links)
- A unified primal dual active set algorithm for nonconvex sparse recovery (Q2038299) (← links)
- A selective overview of deep learning (Q2038303) (← links)
