Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Kaito Shimamura"'
Autor:
Kaito Shimamura, Shuichi Kawano
Publikováno v:
Computational Statistics. 36:2671-2699
Sparse convex clustering is to group observations and conduct variable selection simultaneously in the framework of convex clustering. Although a weighted $$L_1$$ L 1 norm is usually employed for the regularization term in sparse convex clustering, i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0271ef0ed29eef79efdb063bbf05fb14
https://doi.org/10.1007/s00180-021-01101-7
https://doi.org/10.1007/s00180-021-01101-7
Publikováno v:
Intelligent Decision Technologies ISBN: 9789811627644
KES-IDT
KES-IDT
In linear regression models, fusion of coefficients is used to identify predictors having similar relationships with a response. This is called variable fusion. This paper presents a novel variable fusion method in terms of Bayesian linear regression
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c024b6a9aca559fdd304ea918f4debe
https://doi.org/10.1007/978-981-16-2765-1_41
https://doi.org/10.1007/978-981-16-2765-1_41
Publikováno v:
Communications in Statistics - Theory and Methods. 48:4132-4153
The fused lasso penalizes a loss function by the $L_1$ norm for both the regression coefficients and their successive differences to encourage sparsity of both. In this paper, we propose a Bayesian generalized fused lasso modeling based on a normal-e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72f38d133c2325c4ee06b2eb556282b2
https://doi.org/10.1080/03610926.2018.1489056
https://doi.org/10.1080/03610926.2018.1489056
Publikováno v:
Journal of the Japanese Society of Computational Statistics. 28:67-82
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04fff41a68f991d7e5a3ef5abc58e5e9
https://doi.org/10.5183/jjscs.1501001_220
https://doi.org/10.5183/jjscs.1501001_220
Publikováno v:
Japanese Journal of Statistics & Data Science; Nov2023, Vol. 6 Issue 2, p705-727, 23p
Autor:
Shimamura, Kaito, Kawano, Shuichi
Publikováno v:
Computational Statistics; Dec2021, Vol. 36 Issue 4, p2671-2699, 29p
Publikováno v:
Communications in Statistics: Theory & Methods; 2019, Vol. 48 Issue 16, p4132-4153, 22p
This book contains selected papers from the KES-IDT-2021 conference, being held as a virtual conference in June 14–16, 2021. The KES-IDT is an interdisciplinary conference with opportunities for the presentation of new research results and discuss