Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1802001_245
Y. Tanaka
As announced by the current editors Wataru Sakamoto and Hiroshi Yadohisa, the English journal of JSCS “Journal of the Japanese Society of Computational Statistics” (JJSCS) closes at this issue (Volume 30, Number 2), and is going to join a new journal “Japanese Journal of Statistics and Data Science” (JJSD) that will start in 2018 as an official journal of the Japanese Federation of Statistical Science Associations (JFSSA). All of six member societies will jointly contribute to the publication of JJSD. JSCS was established in 1986. I played the role of chief editor of JJSCS since then until 1990, and was responsible for the publication of volumes 1 to 3. The major purpose of establishing JSCS was to make a progress in computational statistics in Japan by providing a forum for people working in various aspects of computational statistics, e.g., statisticians engaged in the research and application of statistical theory and methods, computer scientists/engineers engaged in the development of statistical software, and statisticians/data analysts engaged in the analysis of data obtained with surveys, experiments or other means, and provide them opportunities for exchanging information and ideas and, if possible, for finding seeds for joint works among them. For producing better products as well as for getting more valuable outcomes using the products, it is vital to know what the counterpart really wishes between the producers and the users (or consumers) of everything including statistical methods and software. In those days our major interest was in the R & D of statistical program packages (SPP) as described in President Address (JSCS Japanese journal, Volume 1, Number 1) by the first president Chooichiro Asano. I myself was interested in R & D of SPP on personal computers with my colleagues, that is useful both for the data analysis and for the research work of statistical methods. There are three remarkable traditions in JSCS. I like these traditions and think that they have contributed very much to the achievement of the purpose of establishment mentioned above. One is social gathering at the time of scientific meeting. Every time it is organized in such a way that participants can talk freely in a comfortable atmosphere for exchanging information and ideas. The second one is the tradition that president of JSCS is elected alternately from academic and non-academic communities so that both sides will be satisfied equally in a long period. The third one is that it is very positive in international activities, for example, Japan and Korea Conferences, Japan and China Symposia, and also organizing international meetings such as 25 JSCS Symposium in Busan in 2011, two international scientific meetings for 30 Anniversary in Okinawa and Seattle in 2015 and 2016. Since around a decade ago the environment of statistics has been changing due to advances in the computer and information technology, and accordingly it has strong effect on statistical scienc
正如现任编辑Wataru Sakamoto和Hiroshi Yadohisa所宣布的那样，JSCS的英文期刊《journal of the Japanese Society of Computational Statistics》(JJSCS)将于本期(第30卷第2期)结束，并将加入新期刊《japan journal of Statistics and Data Science》(JJSD)，该期刊将于2018年开始作为日本统计科学协会联合会(JFSSA)的官方期刊。所有六个成员协会将共同为JJSD的出版做出贡献。JSCS成立于1986年。从那时起至1990年，我一直担任JJSCS的主编，负责第1卷至第3卷的出版工作。建立JSCS的主要目的是为从事计算统计各方面工作的人员提供一个论坛，例如从事统计理论和方法的研究和应用的统计学家、从事统计软件开发的计算机科学家/工程师、从事分析通过调查、实验或其他手段获得的数据的统计学家/数据分析师，从而在日本的计算统计方面取得进展。为他们提供交流信息和想法的机会，如果可能的话，为他们之间的合作寻找种子。为了生产更好的产品以及使用产品获得更有价值的结果，了解生产者和用户(或消费者)之间的真正愿望是至关重要的，包括统计方法和软件。当时，我们的主要兴趣是开发第一任社长浅野光一郎在《社长演说》(JSCS日文杂志第1卷第1期)中所描述的统计程序包(SPP)。我本人和同事对个人电脑上的SPP的研发很感兴趣，这对数据分析和统计方法的研究工作都很有用。JSCS有三个显著的传统。我喜欢这些传统，并认为它们对实现上述建立的目的做出了很大贡献。一是科学会议期间的社交聚会。每次会议的组织方式都是这样的，参与者可以在一个舒适的氛围中自由交谈，交换信息和想法。二是JSCS的主席由学术界和非学术界交替选举产生的传统，使双方在长期内都能感到满意。第三，在国际活动中非常积极，例如，日本和韩国会议，日本和中国研讨会，以及2011年在釜山举办的25 JSCS研讨会，2015年和2016年在冲绳和西雅图举办的30周年国际科学会议。大约十年前以来，由于计算机和信息技术的进步，统计环境发生了变化，因此它对统计科学特别是计算统计产生了强烈的影响。让我们简要回顾一下所发生的事情。
{"title":"COMMENT: ON CLOSING OF ENGLISH JOURNAL OF JSCS AND THE BIRTH OF NEW JOURNAL JJSD","authors":"Y. Tanaka","doi":"10.5183/JJSCS.1802001_245","DOIUrl":"https://doi.org/10.5183/JJSCS.1802001_245","url":null,"abstract":"As announced by the current editors Wataru Sakamoto and Hiroshi Yadohisa, the English journal of JSCS “Journal of the Japanese Society of Computational Statistics” (JJSCS) closes at this issue (Volume 30, Number 2), and is going to join a new journal “Japanese Journal of Statistics and Data Science” (JJSD) that will start in 2018 as an official journal of the Japanese Federation of Statistical Science Associations (JFSSA). All of six member societies will jointly contribute to the publication of JJSD. JSCS was established in 1986. I played the role of chief editor of JJSCS since then until 1990, and was responsible for the publication of volumes 1 to 3. The major purpose of establishing JSCS was to make a progress in computational statistics in Japan by providing a forum for people working in various aspects of computational statistics, e.g., statisticians engaged in the research and application of statistical theory and methods, computer scientists/engineers engaged in the development of statistical software, and statisticians/data analysts engaged in the analysis of data obtained with surveys, experiments or other means, and provide them opportunities for exchanging information and ideas and, if possible, for finding seeds for joint works among them. For producing better products as well as for getting more valuable outcomes using the products, it is vital to know what the counterpart really wishes between the producers and the users (or consumers) of everything including statistical methods and software. In those days our major interest was in the R & D of statistical program packages (SPP) as described in President Address (JSCS Japanese journal, Volume 1, Number 1) by the first president Chooichiro Asano. I myself was interested in R & D of SPP on personal computers with my colleagues, that is useful both for the data analysis and for the research work of statistical methods. There are three remarkable traditions in JSCS. I like these traditions and think that they have contributed very much to the achievement of the purpose of establishment mentioned above. One is social gathering at the time of scientific meeting. Every time it is organized in such a way that participants can talk freely in a comfortable atmosphere for exchanging information and ideas. The second one is the tradition that president of JSCS is elected alternately from academic and non-academic communities so that both sides will be satisfied equally in a long period. The third one is that it is very positive in international activities, for example, Japan and Korea Conferences, Japan and China Symposia, and also organizing international meetings such as 25 JSCS Symposium in Busan in 2011, two international scientific meetings for 30 Anniversary in Okinawa and Seattle in 2015 and 2016. Since around a decade ago the environment of statistics has been changing due to advances in the computer and information technology, and accordingly it has strong effect on statistical scienc","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125540238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1702001_234
Masao Ueki
A simple method is presented to enhance statistical power of score tests for regression models via Fisher transformation (or Fisher’s z-transformation) by exploiting a relationship with the partial correlation coefficient. Simulation studies mimicking marginal association and gene-environment interaction analyses for genome-wide association studies (GWASs) under case-control design demonstrate that the Fisher transformation enhances power of the score tests while maintaining type I error asymptotically. The smaller the sample size is, the more the enhancement is pronounced, at the expense of inflated type I error due to invalidating asymptotic approximation. Accordingly, the proposed method may be applied when sample size is enough for valid asymptotic approximation. An illustration with real GWAS data is also presented. 1. Fisher-transformation of score tests for regression models Suppose that n response variables y = (y1, . . . , yn) T and an n × p design matrix X = (x1, . . . ,xn) T are observed, where xi is a p-dimensional column vector of explanatory variables for subject i ∈ {1, . . . , n}. Let f(yi | xi) denote the probability distribution of yi conditional on xi for each i. Here, the probability density function of a continuous random variable or the probability mass function of a discrete random variable is referred to as a probability distribution (Dobson, 2002). Assume that a transformed conditional expectation of yi through some differentiable monotone function (i.e. the link function) is written as xi β, in which β is a vector of corresponding p regression coefficients. Then, denote the loglikelihood by l(xi β) = log f(yi | xi) for the ith sample. Throughout, it is assumed that each yi is independently distributed given xi. The above regression framework includes the generalized linear models (McCullagh and Nelder, 1989; Dobson, 2002) and regression with heavy-tailed error distribution (Lange and Sinsheimer, 1993). Suppose thatX is partitioned into two parts as (X1,X2), where X1 is a collection of q (q < p) explanatory variables to be tested for association with y and X2 is a set of p − q covariates to be adjusted for. Correspondingly, let β = (β1 ,β T 2 ) T and xi = (x T 1,i,x T 2,i) T . In this article, X is assumed to be of full column rank. 1.1. Fisher-transformed score test: single parameter case This subsection considers the case of q = 1, and hence the corresponding regression coefficient is written as β1 with a non-bold letter. In genome-wide association study (GWAS) ∗Biostatistics Center, Kurume University, 67 Asahi-machi, Kurume, Fukuoka 830-0011, Japan. Present affiliation is Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan E-mail: uekimrsd@nifty.com
{"title":"ENHANCING POWER OF SCORE TESTS FOR REGRESSION MODELS VIA FISHER TRANSFORMATION","authors":"Masao Ueki","doi":"10.5183/JJSCS.1702001_234","DOIUrl":"https://doi.org/10.5183/JJSCS.1702001_234","url":null,"abstract":"A simple method is presented to enhance statistical power of score tests for regression models via Fisher transformation (or Fisher’s z-transformation) by exploiting a relationship with the partial correlation coefficient. Simulation studies mimicking marginal association and gene-environment interaction analyses for genome-wide association studies (GWASs) under case-control design demonstrate that the Fisher transformation enhances power of the score tests while maintaining type I error asymptotically. The smaller the sample size is, the more the enhancement is pronounced, at the expense of inflated type I error due to invalidating asymptotic approximation. Accordingly, the proposed method may be applied when sample size is enough for valid asymptotic approximation. An illustration with real GWAS data is also presented. 1. Fisher-transformation of score tests for regression models Suppose that n response variables y = (y1, . . . , yn) T and an n × p design matrix X = (x1, . . . ,xn) T are observed, where xi is a p-dimensional column vector of explanatory variables for subject i ∈ {1, . . . , n}. Let f(yi | xi) denote the probability distribution of yi conditional on xi for each i. Here, the probability density function of a continuous random variable or the probability mass function of a discrete random variable is referred to as a probability distribution (Dobson, 2002). Assume that a transformed conditional expectation of yi through some differentiable monotone function (i.e. the link function) is written as xi β, in which β is a vector of corresponding p regression coefficients. Then, denote the loglikelihood by l(xi β) = log f(yi | xi) for the ith sample. Throughout, it is assumed that each yi is independently distributed given xi. The above regression framework includes the generalized linear models (McCullagh and Nelder, 1989; Dobson, 2002) and regression with heavy-tailed error distribution (Lange and Sinsheimer, 1993). Suppose thatX is partitioned into two parts as (X1,X2), where X1 is a collection of q (q < p) explanatory variables to be tested for association with y and X2 is a set of p − q covariates to be adjusted for. Correspondingly, let β = (β1 ,β T 2 ) T and xi = (x T 1,i,x T 2,i) T . In this article, X is assumed to be of full column rank. 1.1. Fisher-transformed score test: single parameter case This subsection considers the case of q = 1, and hence the corresponding regression coefficient is written as β1 with a non-bold letter. In genome-wide association study (GWAS) ∗Biostatistics Center, Kurume University, 67 Asahi-machi, Kurume, Fukuoka 830-0011, Japan. Present affiliation is Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan E-mail: uekimrsd@nifty.com","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115773510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1707001_236
Kanae Takahashi, Kouji Yamamoto
The performance of randomization methods in consideration of the impact of a prognostic factor that has an interaction and baseline characteristics that have no effect on the outcome has not been clarified, especially for small sized clinical trials. We conducted numerical simulations to identify the difference in behaviour of the empirical power and the empirical type 1 error rate among some randomization methods and statistical analyses when we use a prognostic factor that has an interaction or baseline characteristics that have no effect on the outcome for small sized randomized controlled trials. The empirical power was higher when using a prognostic factor that had an interaction. Also, by using stratified blocked randomization (ST) or minimization (MI) with the multiple regression, the empirical power was further increased. On the other hand, the empirical power was lower when using baseline characteristics that had no effect on the outcome. We recommend conducting ST or MI, multiple regression and using a prognostic factor that has an interaction in small-size randomized controlled trials.
{"title":"THE PERFORMANCE OF RANDOMIZATION METHODS IN CONSIDERATION OF PROGNOSTIC FACTORS FOR SMALL-SIZE CLINICAL TRIALS: A SIMULATION STUDY","authors":"Kanae Takahashi, Kouji Yamamoto","doi":"10.5183/JJSCS.1707001_236","DOIUrl":"https://doi.org/10.5183/JJSCS.1707001_236","url":null,"abstract":"The performance of randomization methods in consideration of the impact of a prognostic factor that has an interaction and baseline characteristics that have no effect on the outcome has not been clarified, especially for small sized clinical trials. We conducted numerical simulations to identify the difference in behaviour of the empirical power and the empirical type 1 error rate among some randomization methods and statistical analyses when we use a prognostic factor that has an interaction or baseline characteristics that have no effect on the outcome for small sized randomized controlled trials. The empirical power was higher when using a prognostic factor that had an interaction. Also, by using stratified blocked randomization (ST) or minimization (MI) with the multiple regression, the empirical power was further increased. On the other hand, the empirical power was lower when using baseline characteristics that had no effect on the outcome. We recommend conducting ST or MI, multiple regression and using a prognostic factor that has an interaction in small-size randomized controlled trials.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127619462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1802002_246
Wataru Sakamoto, Hiroshi Yadohisa
{"title":"ANNOUNCEMENT: ON PUBLICATION OF THE JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE","authors":"Wataru Sakamoto, Hiroshi Yadohisa","doi":"10.5183/JJSCS.1802002_246","DOIUrl":"https://doi.org/10.5183/JJSCS.1802002_246","url":null,"abstract":"","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122537081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1605001_231
Atsushi Yoshida, T. Sakumura, T. Kamakura
We aim at improving the accuracy of indoor position estimation through a statistical approach. In this study, we propose a position estimation method based on Time-of-Arrival (ToA). ToA data are often useful. However, ToA data include a positive bias due to the reflection of radio waves. Therefore, it is difficult to estimate the TAG position from ToA data directly without an accurate bias correction. In this paper, we propose a maximum likelihood estimation method for the TAG position using gamma regression and a rotated distribution, and we show that the estimation with bias correction is more accurate than the estimation without bias correction. In addition, we show that our method also provides a confidence region for the TAG position.
{"title":"INDOOR LOCATION ESTIMATION BASED ON TOA DATA AND BIAS ESTIMATION USING GAMMA REGRESSION","authors":"Atsushi Yoshida, T. Sakumura, T. Kamakura","doi":"10.5183/JJSCS.1605001_231","DOIUrl":"https://doi.org/10.5183/JJSCS.1605001_231","url":null,"abstract":"We aim at improving the accuracy of indoor position estimation through a statistical approach. In this study, we propose a position estimation method based on Time-of-Arrival (ToA). ToA data are often useful. However, ToA data include a positive bias due to the reflection of radio waves. Therefore, it is difficult to estimate the TAG position from ToA data directly without an accurate bias correction. In this paper, we propose a maximum likelihood estimation method for the TAG position using gamma regression and a rotated distribution, and we show that the estimation with bias correction is more accurate than the estimation without bias correction. In addition, we show that our method also provides a confidence region for the TAG position.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131188422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1709000_239
M. Tomita
{"title":"EDITORIAL: SPECIAL FEATURE ON THE 30TH ANNIVERSARY OF JSCS","authors":"M. Tomita","doi":"10.5183/JJSCS.1709000_239","DOIUrl":"https://doi.org/10.5183/JJSCS.1709000_239","url":null,"abstract":"","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129027441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1708001_244
A. Shinozaki, Hiroki Hashiguchi, Toshiya Iwashita
This paper provides an alternative proof of the derivation of the distribution of the largest eigenvalue of an elliptical Wishart matrix in contrast to the result of CaroLopera et al. (2016). We show the relation between multivariate and matrix-variate t distributions. From this relation, we can generate random numbers drawn from the matrix-variate t distribution. A Monte Carlo simulation is conducted to evaluate the accuracy for the truncated distribution function of the largest eigenvalue of the elliptical Wishart matrix. Exact computation of the distribution of the smallest eigenvalue is also presented.
{"title":"DISTRIBUTION OF THE LARGEST EIGENVALUE OF AN ELLIPTICAL WISHART MATRIX AND ITS SIMULATION","authors":"A. Shinozaki, Hiroki Hashiguchi, Toshiya Iwashita","doi":"10.5183/JJSCS.1708001_244","DOIUrl":"https://doi.org/10.5183/JJSCS.1708001_244","url":null,"abstract":"This paper provides an alternative proof of the derivation of the distribution of the largest eigenvalue of an elliptical Wishart matrix in contrast to the result of CaroLopera et al. (2016). We show the relation between multivariate and matrix-variate t distributions. From this relation, we can generate random numbers drawn from the matrix-variate t distribution. A Monte Carlo simulation is conducted to evaluate the accuracy for the truncated distribution function of the largest eigenvalue of the elliptical Wishart matrix. Exact computation of the distribution of the smallest eigenvalue is also presented.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124160935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1706002_235
Kengo Fujisawa, Kouji Tahata
Many observations tend to concentrate in the main diagonal cells when analyzing square contingency tables with ordered categories. Although many statisticians have proposed a variety of symmetry and asymmetry models, constraints on the main diagonal cells are not considered. This implies that the observed frequencies on the main diagonal cells are not utilized. Herein we propose three models that indicate an asymmetric structure for the log odds ratio for cell probabilities. These models constrain the main diagonal cells such that the information in the main diagonal cells can be utilized. Then we decompose the symmetry model using the proposed models.
{"title":"ASYMMETRY MODELS BASED ON LOGIT TRANSFORMATIONS FOR SQUARE CONTINGENCY TABLES WITH ORDINAL CATEGORIES","authors":"Kengo Fujisawa, Kouji Tahata","doi":"10.5183/JJSCS.1706002_235","DOIUrl":"https://doi.org/10.5183/JJSCS.1706002_235","url":null,"abstract":"Many observations tend to concentrate in the main diagonal cells when analyzing square contingency tables with ordered categories. Although many statisticians have proposed a variety of symmetry and asymmetry models, constraints on the main diagonal cells are not considered. This implies that the observed frequencies on the main diagonal cells are not utilized. Herein we propose three models that indicate an asymmetric structure for the log odds ratio for cell probabilities. These models constrain the main diagonal cells such that the information in the main diagonal cells can be utilized. Then we decompose the symmetry model using the proposed models.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131996378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-20DOI: 10.5183/JJSCS.1605003_232
T. Nagai, T. Kamakura
The cone-convex hull by complement (ccc-hull) is a generalized convex hull created from Poincar´e Cones . We propose a new approach with the ccc-hull for the simulation of the extent of damage by a tsunami, and simulate the damaged area at the time of the Great East Japan Earthquake for approximate damage by samples from a two-dimensional Non-homogeneous Poisson Process. Then, we consider the problem of the estimation of the parameter ρ , which corresponds to the opening angle of the Poincar´e Cones. We believe our suggestion can be used to predict the extent of a tsunami in a specified area in Japan.
{"title":"INFERENCE FOR THE EXTENT PARAMETER OF DAMAGE BY TSUNAMI WITH POINCARE CONES","authors":"T. Nagai, T. Kamakura","doi":"10.5183/JJSCS.1605003_232","DOIUrl":"https://doi.org/10.5183/JJSCS.1605003_232","url":null,"abstract":"The cone-convex hull by complement (ccc-hull) is a generalized convex hull created from Poincar´e Cones . We propose a new approach with the ccc-hull for the simulation of the extent of damage by a tsunami, and simulate the damaged area at the time of the Great East Japan Earthquake for approximate damage by samples from a two-dimensional Non-homogeneous Poisson Process. Then, we consider the problem of the estimation of the parameter ρ , which corresponds to the opening angle of the Poincar´e Cones. We believe our suggestion can be used to predict the extent of a tsunami in a specified area in Japan.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126719743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-20DOI: 10.5183/JJSCS.1705001_242
R. Igari, T. Hoshino
In this study, we propose a new estimation procedure for incomplete survival data caused by nonignorable nonresponses or missing censoring indicators. It is widely known that if there is any nonignorable missingness or censoring indicators cannot be fully observed, the results from survival analysis such as the Kaplan-Meier estimator or the Cox proportional hazard model may be biased. However, it sometimes occurs that nonignorable missingness cannot be specified and that the censoring indicators are never or partially observed. We propose a Bayesian generalized method of moments (GMM) approach that utilizes population-level information to identify true survival time and estimates parameters. We apply the proposed model to analyze purchase duration in marketing using purchase history data.
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