Pages that link to "Item:Q5754925"

The following pages link to Prediction by Supervised Principal Components (Q5754925):

Displaying 38 items.

• Cross‐validation and peeling strategies for survival bump hunting using recursive peeling methods (Q4970180) (← links)
• Testing for additivity in nonparametric heteroscedastic regression models (Q4987552) (← links)
• Nonsparse Learning with Latent Variables (Q4994162) (← links)
• Supervised <i>t</i>-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification (Q4995088) (← links)
• (Q5054615) (← links)
• Bayesian principal component regression with data-driven component selection (Q5127030) (← links)
• Independent screening in high-dimensional exponential family predictors’ space (Q5130151) (← links)
• (Q5159462) (← links)
• The Dantzig Discriminant Analysis with High Dimensional Data (Q5177600) (← links)
• Statistical and Knowledge Supported Visualization of Multivariate Data (Q5195006) (← links)
• Assessment of evaluation criteria for survival prediction from genomic data (Q5391153) (← links)
• Pruning a sufficient dimension reduction with a<i>p</i>-value guided hard-thresholding (Q5739663) (← links)
• Comment: Fisher lecture: Dimension reduction in regression (Q5965649) (← links)
• Discussion of: Treelets -- an adaptive multi-scale basis for sparse unordered data (Q5970954) (← links)
• Using sufficient direction factor model to analyze latent activities associated with breast cancer survival (Q6047776) (← links)
• Multinomial logistic factor regression for multi-source functional block-wise missing data (Q6057049) (← links)
• Ensemble Subset Regression (ENSURE): Efficient High-dimensional Prediction (Q6069875) (← links)
• Principal component regression in GAMLSS applied to Greek–German government bond yield spreads (Q6078174) (← links)
• Are bond returns predictable with real-time macro data? (Q6090593) (← links)
• Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models (Q6099122) (← links)
• Using reference models in variable selection (Q6104420) (← links)
• Prediction of sports injuries in football: a recurrent time-to-event approach using regularized Cox models (Q6107409) (← links)
• Distributed Estimation for Principal Component Analysis: An Enlarged Eigenspace Analysis (Q6110700) (← links)
• Optimal discriminant analysis in high-dimensional latent factor models (Q6136589) (← links)
• Mining the factor zoo: estimation of latent factor models with sufficient proxies (Q6150517) (← links)
• Predictive performance of psychological tests: is it better to use items than subscales? (Q6170539) (← links)
• Envelopes and principal component regression (Q6184884) (← links)
• A high-dimensional classification rule using sample covariance matrix equipped with adjusted estimated eigenvalues (Q6541769) (← links)
• Deep spectral Q-learning with application to mobile health (Q6548807) (← links)
• Supervised Principal Component Regression for Functional Responses with High Dimensional Predictors (Q6552547) (← links)
• Are Latent Factor Regression and Sparse Regression Adequate? (Q6567903) (← links)
• Alleviating conditional independence assumption of naive Bayes (Q6581299) (← links)
• Interpretable linear dimensionality reduction based on bias-variance analysis (Q6609081) (← links)
• Nonparametric Estimation and Conformal Inference of the Sufficient Forecasting With a Diverging Number of Factors (Q6620856) (← links)
• Targeting Predictors Via Partial Distance Correlation With Applications to Financial Forecasting (Q6620922) (← links)
• A model-based multithreshold method for subgroup identification (Q6627149) (← links)
• Bayesian latent factor on image regression with nonignorable missing data (Q6627936) (← links)
• Addressing the implementation challenge of risk prediction model due to missing risk factors: the submodel approximation approach (Q6663861) (← links)