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Maximum likelihood estimators for extended growth curve model with orthogonal between-individual design matrices 具有正交设计矩阵的扩展生长曲线模型的极大似然估计
Statistical Methodology Pub Date : 2015-03-01 DOI: 10.1016/j.stamet.2014.09.005
Daniel Klein, Ivan Žežula
{"title":"Maximum likelihood estimators for extended growth curve model with orthogonal between-individual design matrices","authors":"Daniel Klein,&nbsp;Ivan Žežula","doi":"10.1016/j.stamet.2014.09.005","DOIUrl":"10.1016/j.stamet.2014.09.005","url":null,"abstract":"<div><p><span>The extended growth curve model is discussed in this paper. There are two versions of the model studied in the literature, which differ in the way how the column spaces of the design matrices<span> are nested. The nesting is applied either to the between-individual or to the within-individual design matrices. Although both versions are equivalent via reparametrization, the properties of estimators cannot be transferred directly because of non-linearity of estimators. Since in many applications the between-individual matrices are one-way ANOVA matrices, it is reasonable to assume </span></span>orthogonality<span> of the column spaces of between-individual design matrices along with nestedness of the column spaces of within-individual design matrices. We present the maximum likelihood estimators and their basic moments for the model with such orthogonality condition.</span></p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"23 ","pages":"Pages 59-72"},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.09.005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092531","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: 5
On bivariate and a mixture of bivariate Birnbaum–Saunders distributions 关于二元和二元混合Birnbaum-Saunders分布
Statistical Methodology Pub Date : 2015-03-01 DOI: 10.1016/j.stamet.2014.07.001
Mohsen Khosravi , Debasis Kundu , Ahad Jamalizadeh
{"title":"On bivariate and a mixture of bivariate Birnbaum–Saunders distributions","authors":"Mohsen Khosravi ,&nbsp;Debasis Kundu ,&nbsp;Ahad Jamalizadeh","doi":"10.1016/j.stamet.2014.07.001","DOIUrl":"10.1016/j.stamet.2014.07.001","url":null,"abstract":"<div><p><span>Univariate Birnbaum–Saunders distribution has received a considerable amount of attention during the last few years. Recently, Kundu et al. (2010) introduced a bivariate<span> Birnbaum–Saunders distribution. It is observed that the bivariate Birnbaum–Saunders distributions can be written as the weighted mixture of bivariate inverse Gaussian distribution and its reciprocals. In this paper further we introduce a mixture of two bivariate Birnbaum–Saunders distributions and discuss its different properties. The mixture model has eleven parameters, hence it is a very flexible model. The maximum likelihood estimators cannot be obtained in explicit forms. We propose to use the </span></span>EM algorithm to compute the maximum likelihood estimators. It is observed that it saves computational time significantly. We performed some simulation experiments, and one data analysis has been performed to illustrate the EM algorithm. It is observed that the performance of the EM algorithm is quite satisfactory.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"23 ","pages":"Pages 1-17"},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.07.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092426","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: 18
Sequential tests controlling generalized familywise error rates 控制广义家族错误率的顺序测试
Statistical Methodology Pub Date : 2015-03-01 DOI: 10.1016/j.stamet.2014.10.001
Shyamal K. De , Michael Baron
{"title":"Sequential tests controlling generalized familywise error rates","authors":"Shyamal K. De ,&nbsp;Michael Baron","doi":"10.1016/j.stamet.2014.10.001","DOIUrl":"10.1016/j.stamet.2014.10.001","url":null,"abstract":"<div><p><span>Sequential methods are developed for conducting a large number of simultaneous tests while controlling the Type I and Type II </span><em>generalized</em><span> familywise error rates. Namely, for the chosen values of </span><span><math><mi>α</mi></math></span>, <span><math><mi>β</mi></math></span>, <span><math><mi>k</mi></math></span>, and <span><math><mi>m</mi></math></span>, we derive simultaneous tests of <span><math><mi>d</mi></math></span><span> individual hypotheses, based on sequentially collected data, that keep the probability of at least </span><span><math><mi>k</mi></math></span> Type I errors not exceeding level <span><math><mi>α</mi></math></span> and the probability of at least <span><math><mi>m</mi></math></span><span> Type II errors not greater than </span><span><math><mi>β</mi></math></span>. This generalization of the classical notions of familywise error rates allows substantial reduction of the expected sample size of the multiple testing procedure.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"23 ","pages":"Pages 88-102"},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.10.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092548","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: 11
On the Chao and Zelterman estimators in a binomial mixture model 二项混合模型的Chao和Zelterman估计量
Statistical Methodology Pub Date : 2015-01-01 DOI: 10.1016/j.stamet.2014.06.002
Chang Xuan Mao, Nan Yang, Jinhua Zhong
{"title":"On the Chao and Zelterman estimators in a binomial mixture model","authors":"Chang Xuan Mao,&nbsp;Nan Yang,&nbsp;Jinhua Zhong","doi":"10.1016/j.stamet.2014.06.002","DOIUrl":"10.1016/j.stamet.2014.06.002","url":null,"abstract":"<div><p>Data from a surveillance system can be used to estimate the size of a disease population. For certain surveillance systems, a binomial mixture model arises as a natural choice. The Chao estimator estimates a lower bound of the population size. The Zelterman estimator estimates a parameter that is neither a lower bound nor an upper bound. By comparing the Chao estimator and the Zelterman estimator both theoretically and numerically, we conclude that the Chao estimator is better.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"22 ","pages":"Pages 17-22"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.06.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092414","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: 0
A note on the simultaneous confidence intervals for the successive differences of exponential location parameters under heteroscedasticity 异方差条件下指数位置参数连续差异的同时置信区间注记
Statistical Methodology Pub Date : 2015-01-01 DOI: 10.1016/j.stamet.2014.06.001
Mahmood Kharrati-Kopaei
{"title":"A note on the simultaneous confidence intervals for the successive differences of exponential location parameters under heteroscedasticity","authors":"Mahmood Kharrati-Kopaei","doi":"10.1016/j.stamet.2014.06.001","DOIUrl":"10.1016/j.stamet.2014.06.001","url":null,"abstract":"<div><p>In this paper, a lemma is presented and then it is used to construct simultaneous confidence intervals (SCIs) for the differences of location parameters of successive exponential distributions<span> in the unbalanced case under heteroscedasticity<span>. A simulation study based comparison of our SCIs with two recently proposed procedures in terms of coverage probability<span> and average volume revealed that the proposed method can be recommended for small and moderate sample sizes.</span></span></span></p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"22 ","pages":"Pages 1-7"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.06.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092403","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: 10
Incorporating auxiliary information for improved prediction using combination of kernel machines 结合辅助信息改进核机组合预测
Statistical Methodology Pub Date : 2015-01-01 DOI: 10.1016/j.stamet.2014.08.001
Xiang Zhan , Debashis Ghosh
{"title":"Incorporating auxiliary information for improved prediction using combination of kernel machines","authors":"Xiang Zhan ,&nbsp;Debashis Ghosh","doi":"10.1016/j.stamet.2014.08.001","DOIUrl":"10.1016/j.stamet.2014.08.001","url":null,"abstract":"<div><p>With evolving genomic technologies, it is possible to get different measures of the same underlying biological phenomenon using different technologies. The goal of this paper is to build a prediction model for an outcome variable <span><math><mi>Y</mi></math></span><span> from covariates </span><span><math><mi>X</mi></math></span>. Besides <span><math><mi>X</mi></math></span>, we have surrogate covariates <span><math><mi>W</mi></math></span> which are related to <span><math><mi>X</mi></math></span>. We want to utilize the information in <span><math><mi>W</mi></math></span> to boost the prediction for <span><math><mi>Y</mi></math></span> using <span><math><mi>X</mi></math></span>. In this paper, we propose a kernel machine-based method to improve prediction of <span><math><mi>Y</mi></math></span> by <span><math><mi>X</mi></math></span> by incorporating auxiliary information <span><math><mi>W</mi></math></span>. By combining single kernel machines, we also propose a hybrid kernel machine predictor, which can yield a smaller prediction error than its constituents. The prediction error of our kernel machine predictors is evaluated using simulations. We also apply our method to a lung cancer dataset and an Alzheimer’s disease dataset.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"22 ","pages":"Pages 47-57"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.08.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32835018","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: 4
Maximum entropy test for GARCH models GARCH模型的最大熵检验
Statistical Methodology Pub Date : 2015-01-01 DOI: 10.1016/j.stamet.2014.05.002
Jiyeon Lee , Sangyeol Lee , Siyun Park
{"title":"Maximum entropy test for GARCH models","authors":"Jiyeon Lee ,&nbsp;Sangyeol Lee ,&nbsp;Siyun Park","doi":"10.1016/j.stamet.2014.05.002","DOIUrl":"10.1016/j.stamet.2014.05.002","url":null,"abstract":"<div><p>In this paper, we apply the maximum entropy test designed for a goodness of fit in iid samples (cf. Lee et al. (2011)) to GARCH(1,1) models. Its approximate asymptotic distribution is derived under the null hypothesis. A bootstrap version of the test is also discussed and its performance is evaluated through Monte Carlo simulations. A real data analysis is conducted for illustration.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"22 ","pages":"Pages 8-16"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.05.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092388","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: 13
Confidence distributions: A review 信心分布:综述
Statistical Methodology Pub Date : 2015-01-01 DOI: 10.1016/j.stamet.2014.07.002
Saralees Nadarajah , Sergey Bityukov , Nikolai Krasnikov
{"title":"Confidence distributions: A review","authors":"Saralees Nadarajah ,&nbsp;Sergey Bityukov ,&nbsp;Nikolai Krasnikov","doi":"10.1016/j.stamet.2014.07.002","DOIUrl":"10.1016/j.stamet.2014.07.002","url":null,"abstract":"<div><p>A review is provided of the concept <em>confidence distributions</em>. Material covered include: fundamentals, extensions, applications of confidence distributions and available computer software. We expect that this review could serve as a source of reference and encourage further research with respect to confidence distributions.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"22 ","pages":"Pages 23-46"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.07.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092441","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: 23
Modified SCAD penalty for constrained variable selection problems 改进了约束变量选择问题的SCAD惩罚
Statistical Methodology Pub Date : 2014-11-01 DOI: 10.1016/j.stamet.2014.05.001
Chi Tim Ng , Chi Wai Yu
{"title":"Modified SCAD penalty for constrained variable selection problems","authors":"Chi Tim Ng ,&nbsp;Chi Wai Yu","doi":"10.1016/j.stamet.2014.05.001","DOIUrl":"10.1016/j.stamet.2014.05.001","url":null,"abstract":"<div><p>Instead of using sample information only to do variable selection, in this article we also take <em>priori</em><span><span> information — linear constraints<span> of regression coefficients — into account. The penalized likelihood estimation method is adopted. However under constraints, it is not guaranteed that information criteria like </span></span>AIC<span> and BIC are minimized at an oracle solution using the lasso or SCAD penalty. To overcome such difficulties, a modified SCAD penalty is proposed. The definitions of information criteria GCV, AIC and BIC for constrained variable selection problems are also proposed. Statistically, we show that if the tuning parameter is appropriately chosen, the proposed estimators enjoy the oracle properties and satisfy the linear constraints. Additionally, they also possess the robust property to outliers if the linear model with M-estimation is used.</span></span></p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"21 ","pages":"Pages 109-134"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.05.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092370","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: 0
General tests of independence based on empirical processes indexed by functions 基于函数索引的经验过程的一般独立性检验
Statistical Methodology Pub Date : 2014-11-01 DOI: 10.1016/j.stamet.2014.03.001
Salim Bouzebda
{"title":"General tests of independence based on empirical processes indexed by functions","authors":"Salim Bouzebda","doi":"10.1016/j.stamet.2014.03.001","DOIUrl":"10.1016/j.stamet.2014.03.001","url":null,"abstract":"<div><p>The present paper is mainly concerned with the statistical tests of the independence problem between random vectors. We develop an approach based on general empirical processes indexed by a particular class of functions. We prove two abstract approximation theorems<span> that include some existing results as particular cases. Finally, we characterize the limiting behavior of the Möbius transformation of empirical processes indexed by functions under contiguous sequences of alternatives.</span></p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"21 ","pages":"Pages 59-87"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2014.03.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"55092301","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: 9
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