Journal of Statistical Planning and Inference最新文献_第2页

Effect of dimensionality on convergence rates of kernel ridge regression estimator 维度对核脊回归估计器收敛率的影响

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-26 DOI: 10.1016/j.jspi.2024.106228

Kwan-Young Bak, Woojoo Lee

引用次数: 0

Bayes oracle property of multiple tests of multivariate normal means under sparsity 稀疏性条件下多元正态均值多重检验的贝叶斯神谕特性

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-22 DOI: 10.1016/j.jspi.2024.106227

Zikun Qin, Malay Ghosh

引用次数: 0

Assessing heterogeneity in treatment initiation guidelines in longitudinal randomized controlled trials 评估纵向随机对照试验中治疗启动指南的异质性

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-12 DOI: 10.1016/j.jspi.2024.106226

Hyunkeun Ryan Cho , Seonjin Kim

{"title":"Assessing heterogeneity in treatment initiation guidelines in longitudinal randomized controlled trials","authors":"Hyunkeun Ryan Cho , Seonjin Kim","doi":"10.1016/j.jspi.2024.106226","DOIUrl":"10.1016/j.jspi.2024.106226","url":null,"abstract":"<div><p>Treatment initiation guidelines are essential in healthcare, dictating when patients begin therapy. These guidelines are typically assessed through randomized controlled trials (RCTs) to measure their average effect on a population. However, this method may not fully account for patient heterogeneity. We introduce a refined analysis methodology that accounts for diverse times to treatment initiation (TTI) arising from these guidelines. We offer a more detailed perspective on the guidelines’ impact by analyzing homogeneous subpopulations based on their TTI. We develop a longitudinal regression model with smooth time functions to capture dynamic changes in average guideline effects on subpopulations (AGES). A unique weighting mechanism creates pseudo-subpopulations from RCT data, enabling consistent and precise estimation of smooth functions. The efficacy of our approach is validated through theoretical and numerical studies, underscoring its capacity to provide insightful statistical inferences. We exemplify the utility of our methodology by applying it to an RCT of the World Health Organization (WHO) guideline for adults with HIV. This analysis promises to enhance the evaluation of treatment initiation guidelines, leading to more personalized and efficient patient care.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141993852","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

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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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