4 papers
Density Ratio-based Causal Discovery from Bivariate Continuous-Discrete Data
Takashi Nicholas Maeda, Shohei Shimizu, Hidetoshi Matsui
We address the problem of inferring the causal direction between a continuous variable and a discrete variable from observational data. For the model , we adopt th…
Clustering-based aggregate value regression
Kei Hirose, Hidetoshi Matsui, Hiroki Masuda
In various practical situations, forecasting of aggregate values rather than individual ones is often our main focus. For instance, electricity companies are interested in forecast…
Reconciling Functional Data Regression with Excess Bases
Tomoya Wakayama, Hidetoshi Matsui
As the development of measuring instruments and computers has accelerated the collection of massive amounts of data, functional data analysis (FDA) has experienced a surge of atten…
Sparse estimation in ordinary kriging for functional data
Hidetoshi Matsui, Yuya Yamakawa
We introduce a sparse estimation in the ordinary kriging for functional data. The functional kriging predicts a feature given as a function at a location where the data are not obs…