Zobrazeno 1 - 10
of 523
pro vyhledávání: '"Edward J. Wegman"'
Autor:
Mihai, Const.
Publikováno v:
Bulletin mathématique de la Société des Sciences Mathématiques de la République Socialiste de Roumanie, 1988 Jan 01. 32(3), 286-286.
Externí odkaz:
https://www.jstor.org/stable/43681445
Autor:
Barbu, Teodorina
Publikováno v:
Bulletin mathématique de la Société des Sciences Mathématiques de la République Socialiste de Roumanie, 1987 Jan 01. 31(1), 92-92.
Externí odkaz:
https://www.jstor.org/stable/43681311
Autor:
Brillinger, David R.
Publikováno v:
Journal of the American Statistical Association, 1983 Dec 01. 78(384), 986-987.
Externí odkaz:
https://www.jstor.org/stable/2288217
Autor:
Yandell, Brian S.
Publikováno v:
Journal of the American Statistical Association, 1989 Mar 01. 84(405), 338-338.
Externí odkaz:
https://www.jstor.org/stable/2289893
Autor:
Gower, J. C.
Publikováno v:
Journal of the Royal Statistical Society. Series A (General), 1987 Jan 01. 150(4), 405-405.
Externí odkaz:
https://www.jstor.org/stable/2982058
Autor:
Ray, W. D.
Publikováno v:
Journal of the Royal Statistical Society. Series A (General), 1985 Jan 01. 148(1), 63-63.
Externí odkaz:
https://www.jstor.org/stable/2981518
Autor:
Suchismita Goswami, Edward J. Wegman
Publikováno v:
J Appl Stat
Considerable efforts have been made to apply scan statistics in detecting fraudulent or excessive activities in dynamic email networks. However, previous studies are mostly based on the fixed and disjoint windows, and on the assumption of short-term
Publikováno v:
Statistics of Quality ISBN: 9781003067559
Statistics of Quality
Statistics of Quality
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05d5ba4126b20edb9342e85b78feb83b
https://doi.org/10.1201/9781003067559-13
https://doi.org/10.1201/9781003067559-13
Autor:
Amir H. Gandjbakhche, Victor Chernomordik, Afrouz Anderson, Ramon Diaz-Arrastia, Nader Shahni Karamzadeh, Franck Amyot, Eric M. Wassermann, Claude Boccara, Edward J. Wegman, Hadis Dashtestani, Fatima Chowdhry, Kimbra Kenney
Publikováno v:
Brain and Behavior
Background We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task‐related hemodynamic response
Autor:
Edward J. Wegman, Suchismita Goswami
Publikováno v:
Journal of Statistical Science and Application. 4