SURE estimates for high dimensional classification
From MaRDI portal
Publication:4970345
DOI10.1002/sam.11472OpenAlexW3042611118MaRDI QIDQ4970345
Publication date: 14 October 2020
Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/sam.11472
Related Items (1)
Uses Software
Cites Work
- PCA consistency for the power spiked model in high-dimensional settings
- Regularization through variable selection and conditional MLE with application to classification in high dimensions
- High-dimensional classification using features annealed independence rules
- On the optimality of the simple Bayesian classifier under zero-one loss
- Class prediction by nearest shrunken centroids, with applications to DNA microarrays.
- Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
- Support-vector networks
- General maximum likelihood empirical Bayes estimation of normal means
- Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means
- High-dimensional classification via nonparametric empirical Bayes and maximum likelihood inference
- Penalized Classification using Fisher’s Linear Discriminant
- A direct approach to sparse discriminant analysis in ultra-high dimensions
- Tweedie’s Formula and Selection Bias
- Sparse Quadratic Discriminant Analysis For High Dimensional Data
- SURE Estimates for a Heteroscedastic Hierarchical Model
- Convex Optimization, Shape Constraints, Compound Decisions, and Empirical Bayes Rules
- Unnamed Item
- Unnamed Item
This page was built for publication: SURE estimates for high dimensional classification
