Pub Date : 2023-04-21DOI: 10.1080/02331888.2023.2203926
Biplab Hawlader, Pradip Kundu, Amarjit Kundu
A fail-safe system is a -out-of-n system whose lifetime is represented by the second-order statistic. This work studies stochastic comparisons of lifetimes of fail-safe systems with dependent and heterogeneous components, where the components are subjected to random shocks instantaneously. The results are derived for a general semiparametric family of distributions of the component lifetimes. We derive sufficient conditions for the comparison results under the usual stochastic order, and we provide counterexamples to show that under those conditions, similar comparisons cannot be made under the hazard rate order.
{"title":"Stochastic comparisons of lifetimes of fail-safe systems with dependent and heterogeneous components under random shocks","authors":"Biplab Hawlader, Pradip Kundu, Amarjit Kundu","doi":"10.1080/02331888.2023.2203926","DOIUrl":"https://doi.org/10.1080/02331888.2023.2203926","url":null,"abstract":"A fail-safe system is a -out-of-n system whose lifetime is represented by the second-order statistic. This work studies stochastic comparisons of lifetimes of fail-safe systems with dependent and heterogeneous components, where the components are subjected to random shocks instantaneously. The results are derived for a general semiparametric family of distributions of the component lifetimes. We derive sufficient conditions for the comparison results under the usual stochastic order, and we provide counterexamples to show that under those conditions, similar comparisons cannot be made under the hazard rate order.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"90 1","pages":"694 - 709"},"PeriodicalIF":1.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91354126","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}
Pub Date : 2023-04-17DOI: 10.1080/02331888.2023.2201504
Yuping Song, Hangyan Li
In this paper, we reconstruct the local linear threshold estimator for the drift coefficient of a semimartingale with jumps. Under mild conditions, we provide the asymptotic normality of our estimator in the presence of finite activity jumps whether the underlying process is Harris recurrent or positive recurrent. Simulation studies for different models show that our estimator performs better than previous research in finite samples, which can correct the boundary bias automatically. Finally, the estimator is illustrated empirically through the stock index from Shanghai Stock Exchange in China under 15-minute high sampling frequency.
{"title":"Bias reduction estimation for drift coefficient in diffusion models with jumps","authors":"Yuping Song, Hangyan Li","doi":"10.1080/02331888.2023.2201504","DOIUrl":"https://doi.org/10.1080/02331888.2023.2201504","url":null,"abstract":"In this paper, we reconstruct the local linear threshold estimator for the drift coefficient of a semimartingale with jumps. Under mild conditions, we provide the asymptotic normality of our estimator in the presence of finite activity jumps whether the underlying process is Harris recurrent or positive recurrent. Simulation studies for different models show that our estimator performs better than previous research in finite samples, which can correct the boundary bias automatically. Finally, the estimator is illustrated empirically through the stock index from Shanghai Stock Exchange in China under 15-minute high sampling frequency.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"19 1","pages":"597 - 616"},"PeriodicalIF":1.9,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85622947","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}
Pub Date : 2023-04-12DOI: 10.1080/02331888.2023.2201505
Xudong Zhang, Ting Zhang, Lei Wang
Distributed estimation based on different sources of observations has drawn attention in the modern statistical learning. When the distributed data are missing at random, we propose a two-stage -penalized communication-efficient surrogate likelihood (CSL) algorithm based on inverse probability weighting to eliminate the estimation bias caused by the missing data and construct sparse distributed M-estimator simultaneously. In the first stage, we consider a parametric propensity model and directly apply the -penalized CSL method to obtain an efficient and sparse distributed estimator of the propensity parameter. In the second stage, we construct an IPW-based -penalized CSL loss function to eliminate the bias and obtain the sparse M-estimation. The finite-sample performance of the estimators is studied through simulation, and an application to house sale prices data set is also presented.
{"title":"Two-stage communication-efficient distributed sparse M-estimation with missing data","authors":"Xudong Zhang, Ting Zhang, Lei Wang","doi":"10.1080/02331888.2023.2201505","DOIUrl":"https://doi.org/10.1080/02331888.2023.2201505","url":null,"abstract":"Distributed estimation based on different sources of observations has drawn attention in the modern statistical learning. When the distributed data are missing at random, we propose a two-stage -penalized communication-efficient surrogate likelihood (CSL) algorithm based on inverse probability weighting to eliminate the estimation bias caused by the missing data and construct sparse distributed M-estimator simultaneously. In the first stage, we consider a parametric propensity model and directly apply the -penalized CSL method to obtain an efficient and sparse distributed estimator of the propensity parameter. In the second stage, we construct an IPW-based -penalized CSL loss function to eliminate the bias and obtain the sparse M-estimation. The finite-sample performance of the estimators is studied through simulation, and an application to house sale prices data set is also presented.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"1 1","pages":"617 - 636"},"PeriodicalIF":1.9,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79242492","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}
Pub Date : 2023-03-04DOI: 10.1080/02331888.2023.2201009
Eftychia Solea, Rayan Al Hajj
We study high-dimensional graphical models for non-Gaussian functional data. To relax the Gaussian assumption, we consider the functional Gaussian copula graphical model proposed by Solea and Li [Copula Gaussian graphical models for functional data. J Am Stat Assoc. 2022;117(538):781–793]. To estimate robustly the conditional independence relationships among the functions, we propose a new rank-based correlation operator, the Kendall's tau correlation operator that extends the Kendall's tau correlation matrix at the functional setting. We establish new concentration inequalities and bounds of the rank-based estimator, which guarantee graph estimation consistency. We consider both completely and partially observed functional data, while allowing the graph size to grow with the sample size and accounting for the errors in the estimated functional principal components scores. We illustrate the finite sample properties of our method through simulation studies and a brain data set collected from functional magnetic resonance imaging for ADHD subjects.
{"title":"High-dimensional rank-based graphical models for non-Gaussian functional data","authors":"Eftychia Solea, Rayan Al Hajj","doi":"10.1080/02331888.2023.2201009","DOIUrl":"https://doi.org/10.1080/02331888.2023.2201009","url":null,"abstract":"We study high-dimensional graphical models for non-Gaussian functional data. To relax the Gaussian assumption, we consider the functional Gaussian copula graphical model proposed by Solea and Li [Copula Gaussian graphical models for functional data. J Am Stat Assoc. 2022;117(538):781–793]. To estimate robustly the conditional independence relationships among the functions, we propose a new rank-based correlation operator, the Kendall's tau correlation operator that extends the Kendall's tau correlation matrix at the functional setting. We establish new concentration inequalities and bounds of the rank-based estimator, which guarantee graph estimation consistency. We consider both completely and partially observed functional data, while allowing the graph size to grow with the sample size and accounting for the errors in the estimated functional principal components scores. We illustrate the finite sample properties of our method through simulation studies and a brain data set collected from functional magnetic resonance imaging for ADHD subjects.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"41 1","pages":"388 - 422"},"PeriodicalIF":1.9,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81571098","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}
Pub Date : 2023-03-04DOI: 10.1080/02331888.2023.2177999
Rongfang Yan, Jiale Niu
This manuscript studies the stochastic comparisons of the second-order statistics from dependent or independent and heterogeneous modified proportional hazard rate observations. Some sufficient conditions on the usual stochastic order of the second-order statistics from dependent and heterogeneous observations are established under Archimedean copula. Some sufficient conditions are also provided in the hazard rate order of the second-order statistics arising from two sets of independent and heterogeneous or multiple-outlier modified proportional hazard rate observations. Some numerical examples are given to illustrate the theoretical findings.
{"title":"Stochastic comparisons of second-order statistics from dependent and heterogenous modified proportional hazard rate observations","authors":"Rongfang Yan, Jiale Niu","doi":"10.1080/02331888.2023.2177999","DOIUrl":"https://doi.org/10.1080/02331888.2023.2177999","url":null,"abstract":"This manuscript studies the stochastic comparisons of the second-order statistics from dependent or independent and heterogeneous modified proportional hazard rate observations. Some sufficient conditions on the usual stochastic order of the second-order statistics from dependent and heterogeneous observations are established under Archimedean copula. Some sufficient conditions are also provided in the hazard rate order of the second-order statistics arising from two sets of independent and heterogeneous or multiple-outlier modified proportional hazard rate observations. Some numerical examples are given to illustrate the theoretical findings.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"08 1","pages":"328 - 353"},"PeriodicalIF":1.9,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86496141","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}
Pub Date : 2023-03-04DOI: 10.1080/02331888.2023.2193407
Abedin Haidari, M. Sattari, Ghobad Saadat Kia (Barmalzan), N. Balakrishnan
ABSTRACT For comparing largest order statistics from independent heterogeneous non-negative scale variables in the mean residual life order, a new framework is introduced here. This framework can be viewed as a generalization of the well-known multiple-outlier scale model, and it additionally includes the situation in which all the random variables are heterogeneous. We also find some sufficient conditions for comparing the largest order statistics, one with complete heterogeneous scale parameters and another with homogeneous scale parameters, in the mean residual life order. As examples of the obtained results, generalized gamma, generalized beta of the second kind, power-generalized Weibull, and half-normal distributions are all presented. The findings of this work generalize and also reinforce some of the existing results in this direction.
{"title":"MRL ordering of largest order statistics from heterogeneous scale variables","authors":"Abedin Haidari, M. Sattari, Ghobad Saadat Kia (Barmalzan), N. Balakrishnan","doi":"10.1080/02331888.2023.2193407","DOIUrl":"https://doi.org/10.1080/02331888.2023.2193407","url":null,"abstract":"ABSTRACT For comparing largest order statistics from independent heterogeneous non-negative scale variables in the mean residual life order, a new framework is introduced here. This framework can be viewed as a generalization of the well-known multiple-outlier scale model, and it additionally includes the situation in which all the random variables are heterogeneous. We also find some sufficient conditions for comparing the largest order statistics, one with complete heterogeneous scale parameters and another with homogeneous scale parameters, in the mean residual life order. As examples of the obtained results, generalized gamma, generalized beta of the second kind, power-generalized Weibull, and half-normal distributions are all presented. The findings of this work generalize and also reinforce some of the existing results in this direction.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"7 1","pages":"354 - 374"},"PeriodicalIF":1.9,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80905082","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}
Pub Date : 2023-03-04DOI: 10.1080/02331888.2023.2193748
D. Gaigall
We consider Kolmogorov–Smirnov and Cramér–von-Mises type tests for testing central symmetry, exchangeability, and independence. In the standard case, the tests are intended for the application to independent and identically distributed data with unknown distribution. The tests are available for multivariate data and bootstrap procedures are suitable to obtain critical values. We discuss the applicability of the tests to random effects models, where the random effects are independent but not necessarily identically distributed and with possibly unknown distributions. Theoretical results show the adequacy of the tests in this situation. The quality of the tests in models with random effects is investigated by simulations. Empirical results obtained confirm the theoretical findings. A real data example illustrates the application.
{"title":"On the applicability of several tests to models with not identically distributed random effects","authors":"D. Gaigall","doi":"10.1080/02331888.2023.2193748","DOIUrl":"https://doi.org/10.1080/02331888.2023.2193748","url":null,"abstract":"We consider Kolmogorov–Smirnov and Cramér–von-Mises type tests for testing central symmetry, exchangeability, and independence. In the standard case, the tests are intended for the application to independent and identically distributed data with unknown distribution. The tests are available for multivariate data and bootstrap procedures are suitable to obtain critical values. We discuss the applicability of the tests to random effects models, where the random effects are independent but not necessarily identically distributed and with possibly unknown distributions. Theoretical results show the adequacy of the tests in this situation. The quality of the tests in models with random effects is investigated by simulations. Empirical results obtained confirm the theoretical findings. A real data example illustrates the application.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"338 1","pages":"300 - 327"},"PeriodicalIF":1.9,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76599832","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}
Pub Date : 2023-03-04DOI: 10.1080/02331888.2023.2201010
Ignacio Vidal
The solution of the Montmort's matching problem can be seen as the probability mass function of the number of matches in an experiment for assessing the agreement between nominal variables and gold standard classifications. [Vidal I, de Castro M. A Bayesian analysis of the matching problem. J Stat Plan Inference. 2021;212:194–200] presented a generalization of the Montmort's matching problem by considering the chronological order in what assignments are made and counting the number of unforced errors additionally to the number of matches. These authors carried out a Bayesian analysis of the problem, but in this paper we found a solution of this new approach from a frequentist point of view. We found the bivariate probability mass function of the number of matches and the number of unforced errors. The marginal distribution of the number of unforced errors is computed and expressed in terms of the Stirling numbers of the second kind. Also, some elementary properties were proven, including that the distribution of the unforced errors is equal to that of forced errors. As a practical consequence, we propose a new experiment and a new way of collecting and analysing the data in order to assess the agreement between nominal variables and gold standard classifications. Two real data sets were analysed using the proposed methodology.
蒙特匹配问题的解决方案可以看作是在评估名义变量与金标准分类之间的一致性的实验中匹配数量的概率质量函数。[Vidal I, de Castro M. A]匹配问题的贝叶斯分析。[J] Stat Plan Inference. 2021; 212:194-200]通过考虑分配的时间顺序并将非强制性错误的数量添加到匹配数量中，提出了Montmort匹配问题的泛化。这些作者对这个问题进行了贝叶斯分析，但在本文中，我们从频率论的角度找到了这种新方法的解决方案。我们找到了匹配次数和非强制错误次数的二元概率质量函数。计算了非强迫误差数的边际分布，并用第二类斯特林数表示。此外，还证明了非强迫误差的分布与强迫误差的分布相等等基本性质。作为一个实际的结果，我们提出了一个新的实验和收集和分析数据的新方法，以评估名义变量和金标准分类之间的一致性。使用提出的方法分析了两个真实数据集。
{"title":"Unforced errors in the matching problem","authors":"Ignacio Vidal","doi":"10.1080/02331888.2023.2201010","DOIUrl":"https://doi.org/10.1080/02331888.2023.2201010","url":null,"abstract":"The solution of the Montmort's matching problem can be seen as the probability mass function of the number of matches in an experiment for assessing the agreement between nominal variables and gold standard classifications. [Vidal I, de Castro M. A Bayesian analysis of the matching problem. J Stat Plan Inference. 2021;212:194–200] presented a generalization of the Montmort's matching problem by considering the chronological order in what assignments are made and counting the number of unforced errors additionally to the number of matches. These authors carried out a Bayesian analysis of the problem, but in this paper we found a solution of this new approach from a frequentist point of view. We found the bivariate probability mass function of the number of matches and the number of unforced errors. The marginal distribution of the number of unforced errors is computed and expressed in terms of the Stirling numbers of the second kind. Also, some elementary properties were proven, including that the distribution of the unforced errors is equal to that of forced errors. As a practical consequence, we propose a new experiment and a new way of collecting and analysing the data in order to assess the agreement between nominal variables and gold standard classifications. Two real data sets were analysed using the proposed methodology.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"160 2 1","pages":"496 - 514"},"PeriodicalIF":1.9,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77820235","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}
Pub Date : 2023-03-04DOI: 10.1080/02331888.2023.2185243
Shuli Geng, Lixin Zhang
In longitudinal data analysis, linear models are typically utilized. However, deriving the Bayesian estimation with respect to the misspecification of the correlation structure is a challenging task. In this article, we construct a joint mean–covariance model with angles or hyperspherical coordinates (HPCs) for which we then present a Bayesian framework. Based on the connection with the semipartial correlations (SPCs), we focus on the selection (sparsity) priors on these angles. An efficient Markov chain Monte Carlo (MCMC) algorithm is developed for the proposed model, and the positive definiteness of the correlation matrix in posterior computation is automatically guaranteed by our method. Ultimately, we compare the performance of our joint model with some recent methods focusing only on the correlation matrix by using simulations and clinical trial data on smoking.
{"title":"Bayesian estimation for longitudinal data in a joint model with HPCs","authors":"Shuli Geng, Lixin Zhang","doi":"10.1080/02331888.2023.2185243","DOIUrl":"https://doi.org/10.1080/02331888.2023.2185243","url":null,"abstract":"In longitudinal data analysis, linear models are typically utilized. However, deriving the Bayesian estimation with respect to the misspecification of the correlation structure is a challenging task. In this article, we construct a joint mean–covariance model with angles or hyperspherical coordinates (HPCs) for which we then present a Bayesian framework. Based on the connection with the semipartial correlations (SPCs), we focus on the selection (sparsity) priors on these angles. An efficient Markov chain Monte Carlo (MCMC) algorithm is developed for the proposed model, and the positive definiteness of the correlation matrix in posterior computation is automatically guaranteed by our method. Ultimately, we compare the performance of our joint model with some recent methods focusing only on the correlation matrix by using simulations and clinical trial data on smoking.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"38 1","pages":"375 - 387"},"PeriodicalIF":1.9,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81470890","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}
Pub Date : 2023-02-28DOI: 10.1080/02331888.2023.2183204
Victor Mooto Nawa, S. Nadarajah
Nawa and Nadarajah [Statistics, 2023, doi: 10.1080/02331888.2023.2168004] proposed closed form estimators for a bivariate gamma distribution. But these estimators do not have a direct multivariate extension. In this paper, we propose alternative closed form estimators with direct extensions to the trivariate and multivariate cases. These estimators can have smaller asymptotic variances and smaller asymptotic covariances compared to Zhao et al.'s estimators, method of moments estimators and Nawa and Nadarajah's estimators.
{"title":"Closed form estimators for a multivariate gamma distribution","authors":"Victor Mooto Nawa, S. Nadarajah","doi":"10.1080/02331888.2023.2183204","DOIUrl":"https://doi.org/10.1080/02331888.2023.2183204","url":null,"abstract":"Nawa and Nadarajah [Statistics, 2023, doi: 10.1080/02331888.2023.2168004] proposed closed form estimators for a bivariate gamma distribution. But these estimators do not have a direct multivariate extension. In this paper, we propose alternative closed form estimators with direct extensions to the trivariate and multivariate cases. These estimators can have smaller asymptotic variances and smaller asymptotic covariances compared to Zhao et al.'s estimators, method of moments estimators and Nawa and Nadarajah's estimators.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"1 1","pages":"482 - 495"},"PeriodicalIF":1.9,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83045510","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：