Journal of Statistical Planning and Inference最新文献

Shifted BH methods for controlling false discovery rate in multiple testing of the means of correlated normals against two-sided alternatives 在对相关常模的均值进行双侧替代多重检验时控制误发现率的偏移 BH 方法

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-09-21 DOI: 10.1016/j.jspi.2024.106238

引用次数: 0

On schematic orthogonal arrays of high strength 高强度正交阵列示意图

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-09-04 DOI: 10.1016/j.jspi.2024.106230

引用次数: 0

Zero-inflated multivariate tobit regression modeling 零膨胀多元托比特回归建模

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-09-03 DOI: 10.1016/j.jspi.2024.106229

{"title":"Zero-inflated multivariate tobit regression modeling","authors":"","doi":"10.1016/j.jspi.2024.106229","DOIUrl":"10.1016/j.jspi.2024.106229","url":null,"abstract":"<div><p>A frequent challenge encountered in real-world applications is data having a high proportion of zeros. Focusing on ecological abundance data, much attention has been given to zero-inflated count data. Models for non-negative continuous abundance data with an excess of zeros are rarely discussed. Work presented here considers the creation of a point mass at zero through a left-censoring approach or through a hurdle approach. We incorporate both mechanisms to capture the analog of zero-inflation for count data. Additionally, primary attention has been given to univariate zero-inflated modeling (e.g., single species), whereas data often arise jointly (e.g., a collection of species). With multivariate abundance data, a key issue is to capture dependence among the species at a site, both in terms of positive abundance as well as absence. Therefore, our contribution is a model for multivariate zero-inflated continuous data that are non-negative. Working in a Bayesian framework, we discuss the issue of separating the two sources of zeros and offer model comparison metrics for multivariate zero-inflated data. In an application, we model the total biomass for five tree species obtained from plots established in the Forest Inventory Analysis database in the Northeast region of the United States.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150410","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

Convergent stochastic algorithm for estimation in general multivariate correlated frailty models using integrated partial likelihood 利用集成偏似然法对一般多变量相关虚弱模型进行估计的收敛随机算法

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-08-31 DOI: 10.1016/j.jspi.2024.106231

{"title":"Convergent stochastic algorithm for estimation in general multivariate correlated frailty models using integrated partial likelihood","authors":"","doi":"10.1016/j.jspi.2024.106231","DOIUrl":"10.1016/j.jspi.2024.106231","url":null,"abstract":"<div><p>The Cox model with unspecified baseline hazard is often used to model survival data. In the case of correlated event times, this model can be extended by introducing random effects, also called frailty terms, leading to the frailty model. Few methods have been put forward to estimate parameters of such frailty models, and they often consider only a particular distribution for the frailty terms and specific correlation structures. In this paper, a new efficient method is introduced to perform parameter estimation by maximizing the integrated partial likelihood. The proposed stochastic estimation procedure can deal with frailty models with a broad choice of distributions for the frailty terms and with any kind of correlation structure between the frailty components, also allowing random interaction terms between the covariates and the frailty components. The almost sure convergence of the stochastic estimation algorithm towards a critical point of the integrated partial likelihood is proved. Numerical convergence properties are evaluated through simulation studies and comparison with existing methods is performed. In particular, the robustness of the proposed method with respect to different parametric baseline hazards and misspecified frailty distributions is demonstrated through simulation. Finally, the method is applied to a mastitis and a bladder cancer dataset.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162836","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

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

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

{"title":"Assessing heterogeneity in treatment initiation guidelines in longitudinal randomized controlled trials","authors":"","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

{"title":"A graph decomposition-based approach for the graph-fused lasso","authors":"","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

{"title":"Exponential consistency of M-estimators in generalized linear mixed models","authors":"","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

引用次数: 0