Research

Multivariate Data Analysis for 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 modeling, logit-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
• Decision support systems
• Finance