[1]
Natanegara F; Eli Lilly and Company, Indianapolis, IN, USA. ; Neuenschwander B ; Seaman JW Jr ; Kinnersley N ; Heilmann CR ; Ohlssen D ; Rochester G, in: The current state of Bayesian methods in medical product development: survey results and recommendations from the DIA Bayesian Scientific Working Group. Pharmaceutical Statistics [Pharm Stat] 2014 Jan-Feb; Vol. 13 (1), pp.3-12.
DOI: 10.1002/pst.1595
Google Scholar
[2]
Ando, Tomohiro, in: Bayesian Model Averaging and Bayesian Predictive Information Criterion for Model Selecion, Journal of the Japan Statistical Society. 2008, 38(2): 243-257.
DOI: 10.14490/jjss.38.243
Google Scholar
[3]
SHIOTA, Sayaka ; HASHIMOTO, Kei ; NANKAKU, Yoshihiko ; TOKUDA, Keiichi, in: A Bayesian Framework Using Multiple Model Structures for Speech Recognition. IEICE Transactions on Information and Systems. 2013, E96. D(4): 939-948.
DOI: 10.1587/transinf.e96.d.939
Google Scholar
[4]
YUGE, Tetsushi ; YANAGI, Shigeru, in: Dynamic Fault Tree Analysis Using Bayesian Networks and Sequence Probabilities. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2013, E96. A(5): 953-962.
DOI: 10.1587/transfun.e96.a.953
Google Scholar
[5]
Ando, Tomohiro, in: Bayesian Variable Selection for the Seemingly Unrelated Regression Models with a Large Number of Predictors. JOURNAL OF THE JAPAN STATISTICAL SOCIETY. 2012, 41(2): 187-203.
DOI: 10.14490/jjss.41.187
Google Scholar
[6]
Okada, Kensuke, in: A BAYESIAN APPROACH TO ASYMMETRIC MULTIDIMENSIONAL SCALING. Behaviormetrika. 2012, 39(1): 49-62.
DOI: 10.2333/bhmk.39.49
Google Scholar
[7]
Information on http: /www. hc360. com, 2009-04-25.
Google Scholar