Statistical modelling to treat data with missing value
Statistical modelling to treat data with missing value
批准号:
15500187
负责人:
KIKUCHI Yasuki
金额:
$2.05万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
2003
资助国家:
日本
项目状态:
已结题
起止时间:
2003 至 2005
中文摘要
本研究的目的是建立有效的统计模型,并针对不完全信息(如包含缺失值的数据)的统计推断中估计误差的有效估计方法。将观测信息矩阵和Bootstrap方法得到的方差估计与em -算法得到的泊松混合模型的方差估计进行了比较。Kikuchi和Nomakuchi在日本计算统计学会第17次会议上发表了这一结果(2003.05)。研究了用em -算法对正态混合模型和隐马尔可夫正态模型的参数进行估计,并利用观测到的信息矩阵对估计的方差进行估计。Kikuchi和Nomakuchi将在日本计算统计学会第20次会议上发表这一结果(2006.06)。菊地自2003年起成为厚生劳动省研究项目的研究参与者。我们增加了一个与em算法在临床试验中的应用相关的新主题。我们发展了假设伽玛-威布尔分布和广义伽玛分布的生存函数估计方法。Kikuchi和Nomakuchi在日本计算统计学会第18届会议(2004.05)上发表了这一结果,Kikuchi、Nomakuchi和Anraku在上述研究项目的论文集中发表了题为《EM-algorithm of survival function by EM-algorithm (in Japanese)》的论文。
英文摘要
The purpose of this research was to construct the effective statistical models and to develop the effective method of estimation about the error of the estimates in statistical inference based on incomplete information such as data containing the missing value.We compared the estimates of the variance obtained by the observed information matrix and Bootstrap method for the estimates obtained by EM-algorithm for Poisson mixture model. Kikuchi and Nomakuchi presented this result at the 17th meeting of Japanese Society of Computational Statistics (2003.05).We studied about the estimation of the parameters for normal mixture model and hidden Markov normal model by EM-algorithm and the variance of the estimates by the observed information matrix. Kikuchi and Nomakuchi will present this result at the 20th meeting of Japanese Society of Computational Statistics (2006.06).Kikuchi became the research partaker of the research project of Ministry of Health, Labour and Welfare since 2003. We added a new theme relevant to the application of EM-algorithm to the clinical trial. We developed the method of the estimation of the survival function assuming the Gamma-Weibull distribution and the generalized Gamma distribution. Kikuchi and Nomakuchi presented this result at the 18th meeting of Japanese Society of Computational Statistics (2004.05), and Kikuchi, Nomakuchi and Anraku presented a paper about this result entitled "Estimation of the survival function by EM-algorithm (in Japanese)" on the collected papers of the above research project.
期刊论文(43)
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Does GEM Converge to MLE under Wu's Conditions A Counter Example-
在吴的条件下,GEM 是否收敛于 MLE 反例-
DOI:
--
发表时间:
2005
期刊:
Bulletin of Informatics and Cybernetics Vol.36(To appear)
影响因子:
--
作者:
[K.Nomakuchi, K.Nomakuchi, K.Nomakuchi]
通讯作者:
K.Nomakuchi
Y.Maruyama: "Strong representation theorems for bitone sequential decision processes"Optimization Methods and Software. 18・4. 475-489 (2003)
Y.Maruyama:“双音顺序决策过程的强表示定理”18・489(2003)。
DOI:
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发表时间:
期刊:
影响因子:
--
作者:
[]
通讯作者:
結合型逐次決定過程について
关于组合顺序决策过程
DOI:
--
发表时间:
2004
期刊:
京都大学数理解析研究所講究録 Vol.1373
影响因子:
--
作者:
[菊池泰樹, 野間口謙太郎, 安楽和夫, Y.Maruyama, 丸山幸宏]
通讯作者:
丸山幸宏
Strong representation of a discrete decision process by a bitone sequantial decision process
双音序列决策过程对离散决策过程的强表示
DOI:
--
发表时间:
2003
期刊:
Nonlinear Analysis and Convex Analysis, Proceedings of the International Conference, Yokohama Pub.
影响因子:
--
作者:
[大森裕浩, 和合肇, Y.Murayama]
通讯作者:
Y.Murayama
Estimation of the survival function by EM-algorithm (in Japanese).
通过 EM 算法估计生存函数(日语)。
DOI:
--
发表时间:
2004
期刊:
Collected papers of the research project of Ministry of Health, Labor and Welfare,
影响因子:
--
作者:
[Y.Kikuchi, K.Nomakuchi, K.Anraku]
通讯作者:
K.Anraku
共 23 条
Statistical Determination of the No-Observed-Adverse-Effect Levels based on the Information Criteiron under Order Restriction
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批准号:12680318
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项目类别:Grant-in-Aid for Scientific Research (C)
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资助金额:$1.86万
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财政年份:2000
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负责人:KIKUCHI Yasuki
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依托单位:
海外基金