Research topics
Multivariate Data Analysis, Statistical Learning and
Intelligent Data Analysis
- Classification
and regression trees (fast partitioning algorithms, model-based
partitioning, two-stage segmentation, consensus ranking)
- Tree-based
prediction (decision trees, ensembles methods)
- Regression
Modeling (multi-mixture generalized additive models)
- Data
editing (missing data imputation, data fusion, data validation)
- Data
Mining Strategies (web mining, market basket analysis, association rules)
- Categorical
Data Modeling (ML nonsymmetric correspondence
analysis, logit-bilinear and trilinear
modeling, simultaneous latent budget analysis models)
Applications of Research in Statistics
- Web
marketing (Customer Relationship Management)
- Data
warehousing and Exploratory Data Analysis
- Decision
support systems and Predictive Learning
- Finance