Data Science Research Group
An important purpose of multivariate analysis is to identify any relations among many variables based on statistical data. The recent topics in this field are new modeling and statistical causal inference. In this research group, we apply mathematics and computers extensively to study structural equation modeling, graphical modeling, and independent component analysis as well as survival analysis in biostatistics. Our research includes methodological and application aspects.
Yutaka Kano, full professor
■ Kano, Y. and Harada, A. (2000). Stepwise variable selection in factor analysis. Psychometrika. 65(1), 7-22.
■ Kano, Y. (1997). Beyond third-order efficiency. Sankhya. 59(2), 179-197.Postscript
■ Kano, Y. (1990). Noniterative estimation and the choice of the number of factors in exploratory factor analysis. Psychometrika. 55, 277-291.
■ Neuroinformatics Group, University of Helsinki
■ Department of Behaviormetrics, Osaka University
■ Lab for Information-based Learning System, Waseda University