Vector quantization and clustering in the presence of censoring
From MaRDI portal
Publication:495381
DOI10.1016/j.jmva.2015.05.015zbMath1327.62486OpenAlexW380552621MaRDI QIDQ495381
Publication date: 10 September 2015
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2015.05.015
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Single-index regression models with right-censored responses
- The strong law under random censorship
- Sharper bounds for Gaussian and empirical processes
- Mass transportation problems. Vol. 1: Theory. Vol. 2: Applications
- A Dvoretzky-Kiefer-Wolfowitz type inequality for the Kaplan-Meier estimator.
- Weak convergence and empirical processes. With applications to statistics
- Consistent estimation under random censorship when covariables are present
- Strong uniform consistency results of the weighted average of conditional artificial data points
- Uniform in bandwidth consistency of kernel-type function estimators
- Nonparametric Estimation from Incomplete Observations
- A Criterion for Determining the Number of Groups in a Data Set Using Sum-of-Squares Clustering
- Quantization and the method of<tex>k</tex>-means
- The minimax distortion redundancy in empirical quantizer design
- Least squares quantization in PCM
- Comparison of kernel estimators of conditional distribution function and quantile regression under censoring
- The Kaplan–Meier Estimator as an Inverse-Probability-of-Censoring Weighted Average
- Uniform Representation of Product‐Limit Integrals with Applications
This page was built for publication: Vector quantization and clustering in the presence of censoring
