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Volume 39 (2010)
- Issue 2_3 Pages 41-
- Issue 1 Pages 1-
Volume 39, Issue 2_3
Displaying 1-3 of 3 articles from this issue
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Contributed Papers
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Akikuni Matsumoto, Hisayuki Hara, Kazushi Nomura, Kazumitsu Nawata2010 Volume 39 Issue 2_3 Pages 41-58
Published: 2010
Released on J-STAGE: March 10, 2012
JOURNAL OPEN ACCESSWeather derivatives are financial instruments whose payoffs are based on a specified weather event and are used to hedge the financial impact of weather fluctuations. In this article we focus on weather derivatives whose payoffs are based on precipitation and propose Tobit type models for predicting daily precipitation for evaluating such derivatives. Daily precipitation data take nonnegative values and are also zero-inflated. Tobit type models are suitable for such data. We illustrate practical advantage of our models with some data sets. We also apply a proposed model to an evaluation of the prices of some precipitation derivatives and their payoff functions.View full abstractDownload PDF (882K) -
Tetsuji Tonda, Kenichi Satoh, Hirokazu Yanagihara2010 Volume 39 Issue 2_3 Pages 59-70
Published: 2010
Released on J-STAGE: March 10, 2012
JOURNAL OPEN ACCESSVarying coefficients, which might be varying on time, can be used for visualizations or interpretations of covariate effects. Varying coefficient surfaces, which might be varying on location, can be used for spatial data and useful for understanding geographical distribution of covariate effects. The estimator of varying coefficient surface is usually obtained by kernel smoothing methods. Since it is essentially the linear regression around fixed location,constructing a confidence interval or testing null hypothesis for a function of location is difficult.In this paper, we extend an estimating method on varying coefficients, proposed by Satoh and Yanagihara (2010), Satoh, Yanagihara and Kamo (2009), to varying coefficient surfaces using interaction model between covariates and bases on location. The proposed method can be applied for other complicated regression model, and can be easily calculated by the ordinary statistical software package. Other variables, such as measurement time and condition, can be used as a location information. Examples of analysis for spatial data and survival data were illustrated.View full abstractDownload PDF (867K) -
Satoshi Aoki, Tatsuo Otsu, Akimichi Takemura, Yasuhide Numata2010 Volume 39 Issue 2_3 Pages 71-100
Published: 2010
Released on J-STAGE: March 10, 2012
JOURNAL OPEN ACCESSIn this paper we present statistical analysis of data on subject selection by examinees in NCUEE (National Center for University Entrance Examinations) examination in 2006. In NCUEE examinations, exmaminees can choose subjects depending on the university and the department they are applying. As seen from the well publicized news on skipping world history classes in some high schools, the pattern of subject selection is complicated and depends on many factors, incluing geography and sex. Analysis of influences of these factors is important in discussing the university entrance examination and the education in high shools in Japan. In this paper we deal with geographic factors by incorporating effect of individual cells into hierarchical models of contingency tables. We also estimate the influence of sex on selection of science subjects by conditional likelihood method. For confirming these effects we employ Markov chain Monte Carlo methods, in addition to asymptotic approximation.View full abstractDownload PDF (840K)
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