Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Matsui, Hidetoshi"'
Autor:
Wakayama, Tomoya, Matsui, Hidetoshi
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 attention. The FDA methodology treats longitudinal data as a set of functio
Externí odkaz:
http://arxiv.org/abs/2308.01724
Autor:
Matsui, Hidetoshi, Yamakawa, Yuya
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 observed by a linear combination of data observed at other locations. To
Externí odkaz:
http://arxiv.org/abs/2306.15537
Autor:
Tanaka, Shuntaro, Matsui, Hidetoshi
Screening methods are useful tools for variable selection in regression analysis when the number of predictors is much larger than the sample size. Factor analysis is used to eliminate multicollinearity among predictors, which improves the variable s
Externí odkaz:
http://arxiv.org/abs/2306.05702
Publikováno v:
In City and Environment Interactions December 2024 24
Autor:
Matsui, Hidetoshi
Varying-coefficient functional linear models consider the relationship between a response and a predictor, where the response depends not only the predictor but also an exogenous variable. It then accounts for the relation of the predictors and the r
Externí odkaz:
http://arxiv.org/abs/2203.10268
Autor:
Watanabe, Shotaro, Matsui, Hidetoshi
The binary classification problem has a situation where only biased data are observed in one of the classes. In this paper, we propose a new method to approach the positive and biased negative (PbN) classification problem, which is a weakly supervise
Externí odkaz:
http://arxiv.org/abs/2203.05749
Autor:
Matsui, Hidetoshi
We consider the problem of variable selection in varying-coefficient functional linear models, where multiple predictors are functions and a response is a scalar and depends on an exogenous variable. The varying-coefficient functional linear model is
Externí odkaz:
http://arxiv.org/abs/2110.12599
Publikováno v:
In Auris Nasus Larynx February 2024 51(1):132-137
Autor:
Matsui, Hidetoshi
We extend the varying coefficient functional linear model to the nonlinear model and propose a varying coefficient functional additive model. The proposed method can represent the relationship between functional predictors and a scalar response where
Externí odkaz:
http://arxiv.org/abs/2005.12641
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