文献
J-GLOBAL ID:201702262457496722
整理番号:17A1635261
完全Bayesおよびグラフィカルlassoに基づくアプローチにおける構造的およびパラメトリック不確実性:心理学的ネットワークにおけるエッジ重みを超えて【Powered by NICT】
Structural and parametric uncertainties in full Bayesian and graphical lasso based approaches: Beyond edge weights in psychological networks
著者 (4件):
Hullam Gabor
(Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest Hungary)
,
Juhasz Gabriella
(MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Budapest, Hungary)
,
Deakin Bill
(Neuroscience and Psychiatry Unit, School of Community Based Medicine, Faculty of Medical and Human Sciences, The University of Manchester, Manchester, UK)
,
Antal Peter
(Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest Hungary)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2017
号:
CIBCB
ページ:
1-8
発行年:
2017年
JST資料番号:
W2441A
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)