Research topics
Data Science, 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
- Statistical
surveys (Customer/Tourist Satisfaction Analysis)
- Web
marketing (Customer Relationship Management)
- Data
warehousing and Exploratory Data Analysis
- Decision
support systems and Predictive Learning
- Finance
