Journal of Statistical Planning and Inference最新文献_第5页

A graph decomposition-based approach for the graph-fused lasso 基于图分解的图融合套索方法

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-10 DOI: 10.1016/j.jspi.2024.106221

Feng Yu , Archer Yi Yang , Teng Zhang

{"title":"A graph decomposition-based approach for the graph-fused lasso","authors":"Feng Yu , Archer Yi Yang , Teng Zhang","doi":"10.1016/j.jspi.2024.106221","DOIUrl":"10.1016/j.jspi.2024.106221","url":null,"abstract":"<div><p>We propose a new algorithm for solving the graph-fused lasso (GFL), a regularized model that operates under the assumption that the signal tends to be locally constant over a predefined graph structure. The proposed method applies a novel decomposition of the objective function for the alternating direction method of multipliers (ADMM) algorithm. While ADMM has been widely used in fused lasso problems, existing works such as the network lasso decompose the objective function into the loss function component and the total variation penalty component. In contrast, based on the graph matching technique in graph theory, we propose a new method of decomposition that separates the objective function into two components, where one component is the loss function plus part of the total variation penalty, and the other component is the remaining total variation penalty. We develop an exact convergence rate of the proposed algorithm by developing a general theory on the local convergence of ADMM. Compared with the network lasso algorithm, our algorithm has a faster exact linear convergence rate (although in the same order as for the network lasso). It also enjoys a smaller computational cost per iteration, thus converges overall faster in most numerical examples.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"235 ","pages":"Article 106221"},"PeriodicalIF":0.8,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096052","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: 0

Exponential consistency of M-estimators in generalized linear mixed models 广义线性混合模型中 M 估计器的指数一致性

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-08 DOI: 10.1016/j.jspi.2024.106222

Andrea Bratsberg , Magne Thoresen , Abhik Ghosh

{"title":"Exponential consistency of M-estimators in generalized linear mixed models","authors":"Andrea Bratsberg , Magne Thoresen , Abhik Ghosh","doi":"10.1016/j.jspi.2024.106222","DOIUrl":"10.1016/j.jspi.2024.106222","url":null,"abstract":"<div><p>Generalized linear mixed models are powerful tools for analyzing clustered data, where the unknown parameters are classically (and most commonly) estimated by the maximum likelihood and restricted maximum likelihood procedures. However, since the likelihood-based procedures are known to be highly sensitive to outliers, M-estimators have become popular as a means to obtain robust estimates under possible data contamination. In this paper, we prove that for sufficiently smooth general loss functions defining the M-estimators in generalized linear mixed models, the tail probability of the deviation between the estimated and the true regression coefficients has an exponential bound. This implies an exponential rate of consistency of these M-estimators under appropriate assumptions, generalizing the existing exponential consistency results from univariate to multivariate responses. We have illustrated this theoretical result further for the special examples of the maximum likelihood estimator and the robust minimum density power divergence estimator, a popular example of model-based M-estimators, in the settings of linear and logistic mixed models, comparing it with the empirical rate of convergence through simulation studies.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"235 ","pages":"Article 106222"},"PeriodicalIF":0.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S037837582400079X/pdfft?md5=852e7e6dbe375fd6c8f548a7fe669070&pid=1-s2.0-S037837582400079X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141990800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A criterion for estimating the largest linear homoscedastic zone in Gaussian data 估计高斯数据中最大线性同余区的标准

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-06 DOI: 10.1016/j.jspi.2024.106223

Jean-Marc Bardet

引用次数: 0

Statistical inference from partially nominated sets: An application to estimating the prevalence of osteoporosis among adult women 从部分提名集进行统计推断：应用于估算成年女性骨质疏松症患病率

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-07-26 DOI: 10.1016/j.jspi.2024.106214

Zeinab Akbari Ghamsari , Ehsan Zamanzade , Majid Asadi

{"title":"Statistical inference from partially nominated sets: An application to estimating the prevalence of osteoporosis among adult women","authors":"Zeinab Akbari Ghamsari , Ehsan Zamanzade , Majid Asadi","doi":"10.1016/j.jspi.2024.106214","DOIUrl":"10.1016/j.jspi.2024.106214","url":null,"abstract":"<div><p>This paper focuses on drawing statistical inference based on a novel variant of maxima or minima nomination sampling (NS) designs. These sampling designs are useful for obtaining more representative sample units from the tails of the population distribution using the available auxiliary ranking information. However, one common difficulty in performing NS in practice is that the researcher cannot obtain a nominated sample unless he/she uniquely determines the sample unit with the highest or the lowest rank in each set. To overcome this problem, a variant of NS, which is called partial nomination sampling, is proposed, in which the researcher is allowed to declare that two or more units are tied in the ranks whenever he/she cannot find the sample unit with the highest or the lowest rank. Based on this sampling design, two asymptotically unbiased estimators are developed for the cumulative distribution function, which is obtained using maximum likelihood and moment-based approaches, and their asymptotic normalities are proved. Several numerical studies have shown that the proposed estimators have higher relative efficiencies than their counterparts in simple random sampling in analyzing either the upper or the lower tail of the parent distribution. The procedures that we developed are then implemented on a real dataset from the Third National Health and Nutrition Examination Survey (NHANES III) to estimate the prevalence of osteoporosis among adult women aged 50 and over. It is shown that in certain circumstances, the techniques that we have developed require only one-third of the sample size needed in SRS to achieve the desired precision. This results in a considerable reduction in time and cost compared to the standard SRS method.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"235 ","pages":"Article 106214"},"PeriodicalIF":0.8,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937766","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: 0

Stable convergence of conditional least squares estimators for supercritical continuous state and continuous time branching processes with immigration 有移民的超临界连续状态和连续时间分支过程的条件最小二乘估计子的稳定收敛性

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-07-22 DOI: 10.1016/j.jspi.2024.106213

Mátyás Barczy

引用次数: 0

Some clustering-based change-point detection methods applicable to high dimension, low sample size data 一些适用于高维度、低样本量数据的基于聚类的变化点检测方法

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-07-16 DOI: 10.1016/j.jspi.2024.106212

Trisha Dawn , Angshuman Roy , Alokesh Manna , Anil K. Ghosh

引用次数: 0

Regression to the mean for overdispersed count data 过度分散计数数据的均值回归

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-07-05 DOI: 10.1016/j.jspi.2024.106211

Kiran Iftikhar , Manzoor Khan , Jake Olivier

{"title":"Regression to the mean for overdispersed count data","authors":"Kiran Iftikhar , Manzoor Khan , Jake Olivier","doi":"10.1016/j.jspi.2024.106211","DOIUrl":"https://doi.org/10.1016/j.jspi.2024.106211","url":null,"abstract":"<div><p>In repeated measurements, regression to the mean (RTM) is a tendency of subjects with observed extreme values to move closer to the mean when measured a second time. Not accounting for RTM could lead to incorrect decisions such as when observed natural variation is incorrectly attributed to the effect of a treatment/intervention. A strategy for addressing RTM is to decompose the <em>total effect</em>, the expected difference in paired random variables conditional on the first being in the tail of its distribution, into regression to the mean and unbiased treatment effects. The unbiased treatment effect can then be estimated by subtraction. Formulae are available in the literature to quantify RTM for Poisson distributed data which are constrained by mean–variance equivalence, although there are many real life examples of overdispersed count data that are not well approximated by the Poisson. The negative binomial can be considered an explicit overdispersed Poisson process where the Poisson intensity is chosen from a gamma distribution. In this study, the truncated bivariate negative binomial distribution is used to decompose the total effect formulae into RTM and treatment effects. Maximum likelihood estimators (MLE) and method of moments estimators are developed for the total, RTM, and treatment effects. A simulation study is carried out to investigate the properties of the estimators and compare them with those developed under the assumption of the Poisson process. Data on the incidence of dengue cases reported from 2007 to 2017 are used to estimate the total, RTM, and treatment effects.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"234 ","pages":"Article 106211"},"PeriodicalIF":0.8,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141606665","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: 0

Oracle-efficient estimation and global inferences for variance function of functional data 函数数据方差函数的 Oracle 高效估计和全局推断

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-07-04 DOI: 10.1016/j.jspi.2024.106210

Li Cai , Suojin Wang

{"title":"Oracle-efficient estimation and global inferences for variance function of functional data","authors":"Li Cai , Suojin Wang","doi":"10.1016/j.jspi.2024.106210","DOIUrl":"https://doi.org/10.1016/j.jspi.2024.106210","url":null,"abstract":"<div><p>A new two-step reconstruction-based moment estimator and an asymptotically correct smooth simultaneous confidence band as a global inference tool are proposed for the heteroscedastic variance function of dense functional data. Step one involves spline smoothing for individual trajectory reconstructions and step two employs kernel regression on the individual squared residuals to estimate each trajectory variability. Then by the method of moment an estimator for the variance function of functional data is constructed. The estimation procedure is innovative by synthesizing spline smoothing and kernel regression together, which allows one not only to apply the fast computing speed of spline regression but also to employ the flexible local estimation and the extreme value theory of kernel smoothing. The resulting estimator for the variance function is shown to be oracle-efficient in the sense that it is uniformly as efficient as the ideal estimator when all trajectories were known by “oracle”. As a result, an asymptotically correct simultaneous confidence band for the variance function is established. Simulation results support our asymptotic theory with fast computation. As an illustration, the proposed method is applied to the analyses of two real data sets leading to a number of discoveries.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"234 ","pages":"Article 106210"},"PeriodicalIF":0.8,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141593789","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: 0

Column expanded Latin hypercube designs 列扩展拉丁超立方设计

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-06-27 DOI: 10.1016/j.jspi.2024.106208

Qiao Wei, Jian-Feng Yang, Min-Qian Liu

引用次数: 0

The impact of misclassification on covariate-adaptive randomized clinical trials with generalized linear models 误分类对使用广义线性模型的协变量自适应随机临床试验的影响

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-06-27 DOI: 10.1016/j.jspi.2024.106209

Tong Wang, Wei Ma

{"title":"The impact of misclassification on covariate-adaptive randomized clinical trials with generalized linear models","authors":"Tong Wang, Wei Ma","doi":"10.1016/j.jspi.2024.106209","DOIUrl":"https://doi.org/10.1016/j.jspi.2024.106209","url":null,"abstract":"<div><p>Covariate-adaptive randomization (CAR) is a type of randomization method that uses covariate information to enhance the comparability between different treatment groups. Under such randomization, the covariate is usually well balanced, i.e., the imbalance between the treatment group and placebo group is controlled. In practice, the covariate is sometimes misclassified. The covariate misclassification affects the CAR itself and statistical inferences after the CAR. In this paper, we examine the impact of covariate misclassification on CAR from two aspects. First, we study the balancing properties of CAR with unequal allocation in the presence of covariate misclassification. We show the convergence rate of the imbalance and compare it with that under true covariate. Second, we study the hypothesis test under CAR with misclassified covariates in a generalized linear model (GLM) framework. We consider both the unadjusted and adjusted models. To illustrate the theoretical results, we discuss the validity of test procedures for three commonly-used GLM, i.e., logistic regression, Poisson regression and exponential model. Specifically, we show that the adjusted model is often invalid when the misclassified covariates are adjusted. In this case, we provide a simple correction for the inflated Type-I error. The correction is useful and easy to implement because it does not require misclassification specification and estimation of the misclassification rate. Our study enriches the literature on the impact of covariate misclassification on CAR and provides a practical approach for handling misclassification.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"234 ","pages":"Article 106209"},"PeriodicalIF":0.8,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141593759","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: 0