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Volume 35, Issue 1
Displaying 1-3 of 3 articles from this issue
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Original Article
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Catch Prediction for Juvenile Bluefin Tuna in the Water Close to Kagoshima Based on Machine LearningHiroshi Shono, Masahiro Horie, Ayumi Inoue, Takeshi Higashi2014 Volume 35 Issue 1 Pages 1-15
Published: August 31, 2014
Released on J-STAGE: October 15, 2014
JOURNAL FREE ACCESSWe conducted the catch prediction for juvenile bluefin tuna in the water close to Kagoshima based on the support vector regression, a kind of statistical machine learning, using catch of juvenile bluefin tuna in other prefectures, skipjack in Kagoshima, marine environment in fishing place like sea surface temperature as input variables. There is a few difference of predicted value in 2011 based on the support vector regression and the corresponding observed one. Prediction accuracy of the model was high. As a result of attribution analysis by using the support vector regression, the influence of catch prediction in other prefectures was wholly larger than that of the factor of marine environmental, especially the impact on catch prediction for juvenile bluefin tuna in Okinawa prefecture was large.View full abstractDownload PDF (1185K) -
Yoshiomi Nakazuru, Takashi Sozu, Chikuma Hamada, Isao Yoshimura2014 Volume 35 Issue 1 Pages 17-35
Published: August 31, 2014
Released on J-STAGE: October 15, 2014
JOURNAL FREE ACCESSThis paper considers clinical trials with multiple endpoints, in which the efficacy of a test treatment is confirmed only when the superiority of the test treatment to control is evidenced in at least 1 endpoint and non-inferiority is observed in the remaining endpoints. Perlman and Wu (2004) proposed a one-sided testing procedure that was adaptable to this type of trials. This paper proposes a modification of this procedure, in which the likelihood ratio test is replaced with another test similar to that proposed by Tang et al. (1989). The performance of the proposed procedure was examined through theoretical consideration and Monte Carlo simulations assuming normality and homoscedasticity. The simulation study demonstrated that the power of the proposed procedure was higher than that of the procedure proposed by Perlman and Wu; in this procedure, type I error rates are maintained within nominal significance levels unless primary endpoints are highly correlated.View full abstractDownload PDF (358K)
Commentaries
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Keiko Sato, Manabu Iwasaki, Hideki Suganami, Toshiya Sato, Hiroe Tsuba ...2014 Volume 35 Issue 1 Pages 37-53
Published: August 31, 2014
Released on J-STAGE: October 15, 2014
JOURNAL FREE ACCESSAll statisticians are expected to produce statistical outcomes of high quality and reliability. To ensure reliability in statistical performance and outcomes and to meet societal expectations, certain standards of conduct (SOC) must be established such that individual statisticians embrace their own principles and so that the community of statisticians as a whole functions with more self-control.
In 2008, the Biometric Society of Japan began revision of the code of conduct, and the working group drafted an SOC. This particular draft re.ected the opinions of statisticians and the basic concepts which aligned well with ethical guidelines of the American Statistical Association and the International Statistical Institute. As forced guidelines rarely result in full compliance and increased ethical conduct, the SOC offers a framework to encourage individual biostatisticians to establish and hold their own principles and to act responsibly with integrity.
The SOC comprises a preamble, mission statement, values, ten principles and background information. The draft SOC was approved by the Council of the Biometric Society of Japan in November 2013.
The SOC will help statisticians improve their capacity to perform sound statistical practices, improve the working environment, cultivate the next generation of statisticians with professionalism, and acquire societal trust.View full abstractDownload PDF (591K)
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