Journal of Statistical Planning and Inference最新文献_第4页

A family of discrete maximum-entropy distributions 离散最大熵分布系列

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-10-01 DOI: 10.1016/j.jspi.2024.106243

David J. Hessen

引用次数: 0

Risk minimization using robust experimental or sampling designs and mixture of designs 利用稳健的实验或抽样设计以及混合设计最大限度地降低风险

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-09-29 DOI: 10.1016/j.jspi.2024.106241

Ejub Talovic, Yves Tillé

{"title":"Risk minimization using robust experimental or sampling designs and mixture of designs","authors":"Ejub Talovic, Yves Tillé","doi":"10.1016/j.jspi.2024.106241","DOIUrl":"10.1016/j.jspi.2024.106241","url":null,"abstract":"<div><div>For both experimental and sampling designs, the efficiency or balance of designs has been extensively studied. There are many ways to incorporate auxiliary information into designs. However, when we use balanced designs to decrease the variance due to an auxiliary variable, the variance may increase due to an effect which we define as lack of robustness. This robustness can be written as the largest eigenvalue of the variance operator of a sampling or experimental design. If this eigenvalue is large, then it might induce a large variance in the Horvitz–Thompson estimator of the total. We calculate or estimate the largest eigenvalue of the most common designs. We determine lower, upper bounds and approximations of this eigenvalue for different designs. Then, we compare these results with simulations that show the trade-off between efficiency and robustness. Those results can be used to determine the proper choice of designs for experiments such as clinical trials or surveys. We also propose a new and simple method for mixing two sampling designs, which allows to use a tuning parameter between two sampling designs. This method is then compared to the Gram–Schmidt walk design, which also governs the trade-off between robustness and efficiency. A set of simulation studies shows that our method of mixture gives similar results to the Gram–Schmidt walk design while having an interpretable variance matrix.</div></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"236 ","pages":"Article 106241"},"PeriodicalIF":0.8,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142416589","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

Optimal s-level fractional factorial designs under baseline parameterization 基线参数化条件下的最优 s 级分数因子设计

IF 0.8 4区数学

Journal of Statistical Planning and Inference Pub Date : 2024-09-27 DOI: 10.1016/j.jspi.2024.106242

Zhaohui Yan, Shengli Zhao

引用次数: 0

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

Sanat K. Sarkar, Shiyu Zhang

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

Rong Yan, Shanqi Pang, Jing Wang, Mengqian Chen

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

Becky Tang , Henry A. Frye , John A. Silander Jr. , Alan E. Gelfand

{"title":"Zero-inflated multivariate tobit regression modeling","authors":"Becky Tang , Henry A. Frye , John A. Silander Jr. , Alan E. Gelfand","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":"236 ","pages":"Article 106229"},"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

Ajmal Oodally , Luc Duchateau , Estelle Kuhn

{"title":"Convergent stochastic algorithm for estimation in general multivariate correlated frailty models using integrated partial likelihood","authors":"Ajmal Oodally , Luc Duchateau , Estelle Kuhn","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":"236 ","pages":"Article 106231"},"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 0.8 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

{"title":"Effect of dimensionality on convergence rates of kernel ridge regression estimator","authors":"Kwan-Young Bak , Woojoo Lee","doi":"10.1016/j.jspi.2024.106228","DOIUrl":"10.1016/j.jspi.2024.106228","url":null,"abstract":"<div><div>Despite the curse of dimensionality, kernel ridge regression often exhibits good performance in practical applications, even when the dimension is moderately large. However, it has been shown that kernel ridge regression cannot be free from the curse of dimensionality. Until now, the literature on kernel ridge regression has suggested that the gap between theory and practice in relation to dimensionality has not narrowed. In this study, we first investigate when the influence of dimensionality does not significantly affect the convergence rate of the kernel ridge regression. Specifically, we study the convergence rate of <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> risks for the kernel ridge estimator, with a focus on reproducing kernel Hilbert space (RKHS) generated by a product kernel. We show that the univariate optimal convergence rate up to a logarithmic factor in <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> risks can be achieved by controlling the size of the RKHS. The result of a numerical study confirms our theoretical findings.</div></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":"236 ","pages":"Article 106228"},"PeriodicalIF":0.8,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180125","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

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":"235 ","pages":"Article 106226"},"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