Sequential Analysis-Design Methods and Applications最新文献_第10页

Thanks to the Referees 感谢裁判

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-10-02 DOI: 10.1080/07474946.2019.1686938

引用次数: 0

A general theory of purely sequential minimum risk point estimation (MRPE) of a function of the mean in a normal distribution 正态分布中均值函数的纯序列最小风险点估计的一般理论

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-10-02 DOI: 10.1080/07474946.2019.1686885

N. Mukhopadhyay, Zhe Wang

{"title":"A general theory of purely sequential minimum risk point estimation (MRPE) of a function of the mean in a normal distribution","authors":"N. Mukhopadhyay, Zhe Wang","doi":"10.1080/07474946.2019.1686885","DOIUrl":"https://doi.org/10.1080/07474946.2019.1686885","url":null,"abstract":"Abstract A purely sequential minimum risk point estimation (MRPE) methodology with associated stopping time N is designed to come up with a useful estimation strategy. We work under an appropriately formulated weighted squared error loss (SEL) due to estimation of a function of μ, with plus linear cost of sampling from a population having both parameters unknown. A series of important first-order and second-order asymptotic (as c, the cost per unit sample, ) results is laid out including the first-order and second-order efficiency properties. Then, accurate sequential risk calculations are launched, which are then followed by two main results: (i) Theorem 4.1 shows an asymptotic risk efficiency property, and (ii) Theorem 5.1 shows an asymptotic second-order regret expansion associated with the proposed purely sequential MRPE strategy assuming suitable conditions on g(.). We also provide a bias-corrected version of the terminal estimator, We follow up with a number of interesting illustrations where Theorems 4.1–5.1 are readily exploited to conclude an asymptotic risk efficiency property and second-order regret expansion, respectively. A number of other interesting illustrations are highlighted where it is possible to verify the conclusions from Theorems 4.1–5.1 more directly with less stringent assumptions on the pilot sample size.","PeriodicalId":48879,"journal":{"name":"Sequential Analysis-Design Methods and Applications","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2019-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/07474946.2019.1686885","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45421026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Sequential tracking of an unobservable two-state Markov process under Brownian noise 布朗噪声下不可观测两态马尔可夫过程的顺序跟踪

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-08-03 DOI: 10.1080/07474946.2021.1847924

A. Muravlev, M. Urusov, M. Zhitlukhin

引用次数: 1

On the convergence rate of the quasi- to stationary distribution for the Shiryaev-Roberts diffusion 关于Shiryaev-Roberts扩散的拟平稳分布的收敛速度

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-05 DOI: 10.1080/07474946.2020.1766926

Kexuan Li, Aleksey S. Polunchenko

引用次数: 2

A hybrid Bayesian-frequentist predictive design for monitoring multi-stage clinical trials 用于监测多阶段临床试验的混合贝叶斯频率预测设计

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI: 10.1080/07474946.2019.1648919

Z. Djeridi, H. Merabet

引用次数: 1

Second-order analysis of regret for sequential estimation of the autoregressive parameter in a first-order autoregressive model 一阶自回归模型中自回归参数序列估计的二阶后悔分析

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI: 10.1080/07474946.2019.1648933

T. N. Sriram, S. Samadi

引用次数: 1

Monitoring a Poisson process subject to gradual changes in the arrival rates 监测到达率逐渐变化的泊松过程

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI: 10.1080/07474946.2019.1648923

Marlo Brown

引用次数: 2

A Khmaladze-transformed test of fit with ML estimation in the presence of recurrent events 在存在重复事件的情况下，用ML估计拟合的khmaladze变换检验

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI: 10.1080/07474946.2019.1648920

K. Zamba, A. Adekpedjou

{"title":"A Khmaladze-transformed test of fit with ML estimation in the presence of recurrent events","authors":"K. Zamba, A. Adekpedjou","doi":"10.1080/07474946.2019.1648920","DOIUrl":"https://doi.org/10.1080/07474946.2019.1648920","url":null,"abstract":"Abstract This article provides a goodness-of-fit test for the distribution function or the survival function in a recurrent event setting, when the inter-event time parametric structure is estimated from the observed data. Of concern is the null hypothesis that the inter-event time distribution is absolutely continuous and belongs to a parametric family , where the q-dimensional parameter space is neither known nor specified. We proposed a Khmaladze martingale-transformed type of test (Khmaladze, 1981), adapted to recurrent events. The test statistic combines two likelihood sources of estimation to form a parametric empirical process: (1) a product-limit nonparametric maximum likelihood estimator (NPMLE; Peña et al., 2001a) that is a consistent estimator of F, say, and (2) a point process likelihood estimator (Jacod, 1974/1975). These estimators are combined to construct a Kolmogorov-Smirnov (KS) type of test (Kolmogorov 1933; Smirnov, 1933). Empirical process and martingale weak convergence frameworks are utilized for theoretical derivations and motivational justification of the proposed transformation. A simulation study is conducted for performance assessment, and the test is applied to a problem investigated by Proschan (1963) on air-conditioning failure in a fleet of Boeing 720 jets.","PeriodicalId":48879,"journal":{"name":"Sequential Analysis-Design Methods and Applications","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/07474946.2019.1648920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47419143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Minimum risk sequential point estimation of the stress-strength reliability parameter for exponential distribution 指数分布下应力-强度可靠性参数的最小风险序贯点估计

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI: 10.1080/07474946.2019.1649347

E. Mahmoudi, Ashkan Khalifeh, V. Nekoukhou

{"title":"Minimum risk sequential point estimation of the stress-strength reliability parameter for exponential distribution","authors":"E. Mahmoudi, Ashkan Khalifeh, V. Nekoukhou","doi":"10.1080/07474946.2019.1649347","DOIUrl":"https://doi.org/10.1080/07474946.2019.1649347","url":null,"abstract":"Abstract In this article, using purely and two-stage sequential procedures, the problem of minimum risk point estimation of the reliability parameter (R) under the stress–strength model, in case the loss function is squared error plus sampling cost, is considered when the random stress (X) and the random strength (Y) are independent and both have exponential distributions with different scale parameters. The exact distribution of the total sample size and explicit formulas for the expected value and mean squared error of the maximum likelihood estimator of the reliability parameter under the stress–strength model are provided under the two-stage sequential procedure. Using the law of large numbers and Monte Carlo integration, the exact distribution of the stopping rule under the purely sequential procedure is approximated. Moreover, it is shown that both proposed sequential procedures are finite and for special cases the exact distribution of stopping times has a degenerate distribution at the initial sample size. The performances of the proposed methodologies are investigated with the help of simulations. Finally, using a real data set, the procedures are clearly illustrated.","PeriodicalId":48879,"journal":{"name":"Sequential Analysis-Design Methods and Applications","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/07474946.2019.1649347","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44062906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

A k-stage procedure for estimating the mean vector of a multivariate normal population 估计多元正态总体的平均向量的k阶段程序

IF 0.8 4区数学

Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI: 10.1080/07474946.2019.1648926

Ajit Chaturvedi, Sudeep R. Bapat, Neeraj Joshi

引用次数: 3