Journal of the Japan Statistical Society. Japanese issue最新文献_第5页

AN APPROXIMATE MOVING AVERAGE REPRESENTATION OF THE PERIODIC STOCHASTIC PROCESS 周期随机过程的近似移动平均表示

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2013-08-08 DOI: 10.14490/JJSS.43.1

H. Kato

引用次数: 1

Twofold structure of duality in Bayesian model averaging 贝叶斯模型平均中对偶的双重结构

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2013-08-08 DOI: 10.14490/JJSS.43.29

Toshio Ohnishi, T. Yanagimoto

引用次数: 2

Principal Components Regression by using Generalized Principal Components Analysis 用广义主成分分析法进行主成分回归

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2013-08-08 DOI: 10.14490/JJSS.43.57

Masakazu Fujiwara, T. Minamidani, Isamu Nagai, H. Wakaki

引用次数: 0

Pseudo Best Estimator by a Separable Approximation of Spatial Covariance Structures 空间协方差结构的可分离逼近伪最佳估计

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-12-29 DOI: 10.14490/JJSS.44.43

Toshihiro Hirano

{"title":"Pseudo Best Estimator by a Separable Approximation of Spatial Covariance Structures","authors":"Toshihiro Hirano","doi":"10.14490/JJSS.44.43","DOIUrl":"https://doi.org/10.14490/JJSS.44.43","url":null,"abstract":"We consider the linear regression model with a spatially correlated error term on a lattice process. When we estimate coefficients in the linear regression model, the generalized least squares estimator (GLSE) is used if the covariance structures are known. However, the GLSE for large spatial data sets is impractically time-consuming because it includes the inversion of the covariance matrix of error terms in different spatial points that is the size of the number of observations. To reduce the computational complexity, we propose the pseudo best estimator (PBE) using spatial covariance structures approximated by separable covariance functions. We derive the asymptotic covariance matrix of the PBE and compare it with those of the least squares estimator (LSE) and the GLSE through some simulations. They also imply that the effect of the misspecification of the covariance matrix for the GLSE is examined. Monte Carlo simulations demonstrate the improvement of the LSE, which does not contain the information of the spatial covariance structure, by the PBE using separable covariance functions even if the true process has an isotropic Matern covariance function. Additionally our proposed PBE is computationally efficient relative to the GLSE for large spatial data sets.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130521639","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}

引用次数: 1

Robustness of a Two-Stage Estimation Procedure when Variances are Unequal 方差不等时两阶段估计过程的鲁棒性

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-12-01 DOI: 10.14490/JJSS.42.207

Y. Takada, Katuya Miyama

引用次数: 1

Detection of Ecological Disturbances to Seabed Fauna through Change of Weight Distribution 重量分布变化对海底动物生态干扰的探测

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-12-01 DOI: 10.14490/JJSS.42.185

Mayumi Naka, R. Shibata, R. Darnell

引用次数: 2

ROBUST REGRESSION FOR FUNCTIONAL TIME SERIES DATA 函数时间序列数据的鲁棒回归

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-12-01 DOI: 10.14490/JJSS.42.125

M. Attouch, Ali Laksaci, E. O. Saïd

引用次数: 15

ASYMPTOTIC EXPANSION OF THE PERCENTILES FOR A SAMPLE MEAN STANDARDIZED BY GMD IN A NORMAL CASE WITH APPLICATIONS 在正常情况下用GMD标准化的样本均值的百分位数的渐近展开式

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-12-01 DOI: 10.14490/JJSS.42.165

N. Mukhopadhyay, Bhargab Chattopadhyay

引用次数: 3

Profile Analysis with Random-Effects Covariance Structure 随机效应协方差结构的剖面分析

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-12-01 DOI: 10.14490/JJSS.42.145

M. Srivastava, M. Singull

引用次数: 8

Simultaneous Bayesian Inference for Longitudinal Data with Asymmetry, Left-censoring and Covariates Measured with Errors 纵向数据不对称、左截距和协变量测量误差的同时贝叶斯推断

Journal of the Japan Statistical Society. Japanese issue Pub Date : 2012-09-04 DOI: 10.14490/JJSS.42.1

Yangxin Huang, G. Dagne

{"title":"Simultaneous Bayesian Inference for Longitudinal Data with Asymmetry, Left-censoring and Covariates Measured with Errors","authors":"Yangxin Huang, G. Dagne","doi":"10.14490/JJSS.42.1","DOIUrl":"https://doi.org/10.14490/JJSS.42.1","url":null,"abstract":"It is a common practice to analyze complex longitudinal data using flexible nonlinear mixed-effects (NLME) models with normality assumption. However, a serious departure of normality may cause lack of robustness and subsequently lead to invalid inference and unreasonable estimates. Covariates are usually introduced in such models to partially explain inter-subject variations, but some covariates may be often measured with substantial errors. Moreover, the response observations may be subject to left-censoring due to a detection limit. Inferential procedures can be complicated dramatically when data with asymmetric (skewed) characteristics, leftcensoring and measurement errors are observed. In the literature, there has been considerable interest in accommodating either skewness, censoring or covariate measurement errors in such models, but there is relatively little work concerning all of the three features simultaneously. In this article, we jointly investigate a skew-t NLME model for response (with left-censoring) process and a skew-t nonparametric mixedeffects model for covariate (with measurement errors) process. We propose a robust skew-t Bayesian modeling approach in a general form to analyze data in capturing the effects of skewness, censoring and measurement errors in covariates simultaneously. A real data example is offered to illustrate the methodologies. The proposed modeling alternative offers important advantages in the sense that the model can be easily fitted in freely available software and the computational effort for the model with a skew-t distribution is almost equivalent to that of the model with a standard normal distribution.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127777801","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}

引用次数: 1