Code
01T02612
Duration
01 March 2013 → 31 August 2014
Funding
Regional and community funding: Special Research Fund
Promotor
Research disciplines
-
Natural sciences
- Applied mathematics in specific fields
- Statistics
- Numerical methods
Keywords
categorical covariates
resampling methods
model selection
robust inference
missing data
Project description
Development of model building, model selection, confidence intervals, testing, and prediction methods for the robust and efficient tau-estimators. Extend tau-estimators and robust LARS so that they can handle categorical covariates and missing data. Robust inference procedures will be based on robust and computationally efficient resampling methods.