Scandinavian Journal of Statistics最新文献_第7页

Truncated two‐parameter Poisson‐Dirichlet approximation for Pitman‐Yor process hierarchical models Pitman - Yor过程分层模型的截断双参数泊松-狄利克雷近似

4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-09-28 DOI: 10.1111/sjos.12688

Junyi Zhang, Angelos Dassios

Abstract In this paper, we construct an approximation to the Pitman–Yor process by truncating its two‐parameter Poisson–Dirichlet representation. The truncation is based on a decreasing sequence of random weights, thus having a lower approximation error compared to the popular truncated stick‐breaking process. We develop an exact simulation algorithm to sample from the approximation process and provide an alternative MCMC algorithm for the parameter regime where the exact simulation algorithm becomes slow. The effectiveness of the simulation algorithms is demonstrated by the estimation of the functionals of a Pitman–Yor process. Then we adapt the approximation process into a Pitman–Yor process mixture model and devise a blocked Gibbs sampler for posterior inference.

摘要本文通过截断Pitman-Yor过程的两参数泊松-狄利克雷表示，构造了一个近似。截断基于随机权重的递减序列，因此与流行的截断木棍断裂过程相比，具有更低的近似误差。我们开发了一种精确的模拟算法来从近似过程中采样，并为精确模拟算法变得缓慢的参数区提供了一种替代的MCMC算法。通过对Pitman-Yor过程的函数估计，证明了仿真算法的有效性。然后，我们将近似过程改编为Pitman-Yor过程混合模型，并设计了一个闭塞的Gibbs采样器进行后验推理。

引用次数: 0

Generalizing the information content for stepped wedge designs: A marginal modeling approach. 推广阶梯楔形设计的信息含量：边际建模法

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-09-01 Epub Date: 2022-09-23 DOI: 10.1111/sjos.12615

Fan Li, Jessica Kasza, Elizabeth L Turner, Paul J Rathouz, Andrew B Forbes, John S Preisser

Stepped wedge trials are increasingly adopted because practical constraints necessitate staggered roll-out. While a complete design requires clusters to collect data in all periods, resource and patient-centered considerations may call for an incomplete stepped wedge design to minimize data collection burden. To study incomplete designs, we expand the metric of information content to discrete outcomes. We operate under a marginal model with general link and variance functions, and derive information content expressions when data elements (cells, sequences, periods) are omitted. We show that the centrosymmetric patterns of information content can hold for discrete outcomes with the variance-stabilizing link function. We perform numerical studies under the canonical link function, and find that while the patterns of information content for cells are approximately centrosymmetric for all examined underlying secular trends, the patterns of information content for sequences or periods are more sensitive to the secular trend, and may be far from centrosymmetric.

阶梯楔形试验之所以被越来越多地采用，是因为实际条件的限制需要交错推出。虽然完整的设计要求分组收集所有时期的数据，但出于资源和以患者为中心的考虑，可能需要采用不完整的阶梯楔形设计，以尽量减轻数据收集负担。为了研究不完全设计，我们将信息内容的度量标准扩展到离散结果。我们在具有一般联系和方差函数的边际模型下进行操作，并推导出数据元素（单元、序列、时段）被省略时的信息含量表达式。我们表明，信息含量的中心对称模式可以在具有方差稳定链接函数的离散结果中成立。我们在典型链接函数下进行了数值研究，发现对于所有考察过的基本世俗趋势，单元的信息含量模式近似于中心对称，而序列或周期的信息含量模式对世俗趋势更为敏感，可能远非中心对称。

{"title":"Generalizing the information content for stepped wedge designs: A marginal modeling approach.","authors":"Fan Li, Jessica Kasza, Elizabeth L Turner, Paul J Rathouz, Andrew B Forbes, John S Preisser","doi":"10.1111/sjos.12615","DOIUrl":"10.1111/sjos.12615","url":null,"abstract":"<p><p>Stepped wedge trials are increasingly adopted because practical constraints necessitate staggered roll-out. While a complete design requires clusters to collect data in all periods, resource and patient-centered considerations may call for an incomplete stepped wedge design to minimize data collection burden. To study incomplete designs, we expand the metric of information content to discrete outcomes. We operate under a marginal model with general link and variance functions, and derive information content expressions when data elements (cells, sequences, periods) are omitted. We show that the centrosymmetric patterns of information content can hold for discrete outcomes with the variance-stabilizing link function. We perform numerical studies under the canonical link function, and find that while the patterns of information content for cells are approximately centrosymmetric for all examined underlying secular trends, the patterns of information content for sequences or periods are more sensitive to the secular trend, and may be far from centrosymmetric.</p>","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/1d/a8/nihms-1850902.PMC10434823.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10490391","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

Marginal additive models for population‐averaged inference in longitudinal and cluster‐correlated data 纵向和聚类相关数据中的群体平均推理的边际加性模型

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-08-10 DOI: 10.1111/sjos.12681

Glen Mcgee, Alex Stringer

We propose a novel marginal additive model (MAM) for modelling cluster‐correlated data with non‐linear population‐averaged associations. The proposed MAM is a unified framework for estimation and uncertainty quantification of a marginal mean model, combined with inference for between‐cluster variability and cluster‐specific prediction. We propose a fitting algorithm that enables efficient computation of standard errors and corrects for estimation of penalty terms. We demonstrate the proposed methods in simulations and in application to (i) a longitudinal study of beaver foraging behaviour, and (ii) a spatial analysis of Loaloa infection in West Africa.This article is protected by copyright. All rights reserved.

引用次数: 0

Design for order‐of‐addition experiments with two‐level components 设计的顺序加法实验与两个水平的组件

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-08-07 DOI: 10.1111/sjos.12678

Hengzhen Huang

The statistical design for order‐of‐addition (OofA) experiments has received much recent interest as its potential in determining the optimal sequence of multiple components, for example, the optimal sequence of drug administration for disease treatment. The traditional OofA experiments focus mainly on the sequence effects of components, i.e., the experimenters fix the factor level of each component and observe how the response is affected by varying the sequences of components. However, the components may also have factorial effects in that changing their factor levels in a given sequence can affect the response. In view of this, we consider the design problem for OofA experiments where each component is experimented at two levels. A systematic method is given to construct OofA designs that jointly considers the sequence design and factorial design for all components. By appropriately choosing the sequence and factorial designs, we show that the combination of the two parts results in a balanced design with an economical run size. Moreover, the constructed designs enjoy a number of optimality properties such as D‐, A‐ and E‐optimalities under some empirical models. The design method proposed can be extended to some other practical situations like the number of process variables is different from the number of components, and OofA experiments with multi‐level components.This article is protected by copyright. All rights reserved.

排序加法(OofA)实验的统计设计最近因其在确定多组分的最佳序列方面的潜力而受到广泛关注，例如，疾病治疗的药物给药的最佳顺序。传统的OofA实验主要关注成分的序列效应，即实验者固定每个成分的因子水平，观察不同成分序列对响应的影响。然而，这些成分也可能具有因子效应，即在给定的顺序中改变它们的因子水平可以影响反应。鉴于此，我们考虑OofA实验的设计问题，其中每个组件在两个层次上进行实验。给出了一种系统的构造面向对象结构设计的方法，该方法综合考虑了各组成部分的序列设计和析因设计。通过适当地选择序列和析因设计，我们表明，这两个部分的组合导致一个平衡的设计与经济运行规模。此外，在一些经验模型下，构建的设计具有D‐、a‐和E‐最优性。所提出的设计方法可以推广到工艺变量数与构件数不同的实际情况，以及多层次构件的OofA实验。这篇文章受版权保护。版权所有。

{"title":"Design for order‐of‐addition experiments with two‐level components","authors":"Hengzhen Huang","doi":"10.1111/sjos.12678","DOIUrl":"https://doi.org/10.1111/sjos.12678","url":null,"abstract":"The statistical design for order‐of‐addition (OofA) experiments has received much recent interest as its potential in determining the optimal sequence of multiple components, for example, the optimal sequence of drug administration for disease treatment. The traditional OofA experiments focus mainly on the sequence effects of components, i.e., the experimenters fix the factor level of each component and observe how the response is affected by varying the sequences of components. However, the components may also have factorial effects in that changing their factor levels in a given sequence can affect the response. In view of this, we consider the design problem for OofA experiments where each component is experimented at two levels. A systematic method is given to construct OofA designs that jointly considers the sequence design and factorial design for all components. By appropriately choosing the sequence and factorial designs, we show that the combination of the two parts results in a balanced design with an economical run size. Moreover, the constructed designs enjoy a number of optimality properties such as D‐, A‐ and E‐optimalities under some empirical models. The design method proposed can be extended to some other practical situations like the number of process variables is different from the number of components, and OofA experiments with multi‐level components.This article is protected by copyright. All rights reserved.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45017438","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: 1

Some mechanisms leading to underdispersion: old and new proposals 导致分散不足的一些机制:新旧建议

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-08-07 DOI: 10.1111/sjos.12677

P. Puig, J. Valero, Amanda Fernández-Fontelo

In statistical modelling, it is important to know the mechanisms that cause underdispersion. Several mechanisms that lead to underdispersed count distributions are revisited from new perspectives, and new ones are introduced. These include procedures based on the number of arrivals in arrival processes, such as renewal and pure birth processes and steady‐state distributions of birth‐death processes, like queues with state‐dependent service rates. Weighted Poisson and other well‐known underdispersed distributions are also related to birth‐death processes. Classical and variable binomial thinning mechanisms are also viewed as important procedures for generating underdispersed distributions, which can also generate bivariate count distributions with negative correlation. Some example applications are shown, one of which is related to Biodosimetry.This article is protected by copyright. All rights reserved.

在统计建模中，了解导致分散不足的机制是很重要的。从新的角度重新审视了导致计数分布不足的几种机制，并引入了新的机制。这包括基于到达流程中到达人数的流程，如更新和纯出生流程，以及出生-死亡流程的稳态分布，如服务费率依赖于状态的队列。加权泊松和其他众所周知的欠分散分布也与出生-死亡过程有关。经典和可变二项细化机制也被视为产生欠分散分布的重要过程，这也可以产生负相关的二元计数分布。给出了一些应用实例，其中一个与生物剂量测定有关。这篇文章受版权保护。版权所有。

引用次数: 0

Communication‐efficient low‐dimensional parameter estimation and inference for high‐dimensional Lp‐quantile regression 高维Lp分位数回归的通信高效低维参数估计和推理

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-08-07 DOI: 10.1111/sjos.12683

Junzhuo Gao, Lei Wang

The Lp‐quantile regression generalizes both quantile regression and expectile regression, and has become popular for its robustness and effectiveness especially when 1 < p ≤ 2. In this paper, we consider the data that are inherently distributed and propose two distributed Lp‐quantile regression estimators for a preconceived low‐dimensional parameter in the presence of high‐dimensional extraneous covariates. To handle the impact of high‐dimensional nuisance parameters, we first investigate regularized projection score for estimating low‐dimensional parameter of main interest in Lp‐quantile regression. To deal with the distributed data, we further propose two communication‐efficient surrogate projection score estimators and establish their theoretical properties. The finite‐sample performance of the proposed estimators is studied through simulations and an application to Communities and Crime data set is also presented.This article is protected by copyright. All rights reserved.

Lp‐分位数回归概括了分位数回归和期望回归，并因其稳健性和有效性而广受欢迎，尤其是当1

引用次数: 0

Density estimation and regression analysis on hyperspheres in the presence of measurement error 存在测量误差的超球面密度估计与回归分析

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-08-04 DOI: 10.1111/sjos.12684

Jeong Min Jeon, I. Van Keilegom

This paper studies density estimation and regression analysis with data observed on a general unit hypersphere and contaminated by measurement errors. We establish novel density and regression estimators, and study their asymptotic properties such as the rates of convergence and asymptotic normality. We also provide two types of asymptotic confidence intervals for both density and regression functions. One type is based on the asymptotic normality of their estimators and the other type is based on the empirical likelihood technique. We present practical details on the implementation of our method as well as simulation studies and real data analysis.This article is protected by copyright. All rights reserved.

引用次数: 0

A Nested Semiparametric Method for Case‐Control Study with Missingness 一种用于导弹情况控制研究的嵌套半参数方法

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-08-01 DOI: 10.1111/sjos.12673

Ge Zhao, Yanyuan Ma, Jill S Hasler, S. Damrauer, Michael G. Levin, Jinbo Chen

We propose a nested semiparametric model to analyze a case-control study where genuine case status is missing for some individuals. The concept of a noncase is introduced to allow for the imputation of the missing genuine cases. The odds ratio parameter of the genuine cases compared to controls is of interest. The imputation procedure predicts the probability of being a genuine case compared to a noncase semiparametrically in a dimen-sion reduction fashion. This procedure is flexible, and vastly generalizes the existing methods. We establish the root-n asymptotic normality of the odds ratio parameter estimator. Our method yields stable odds ratio parameter estimation owing to the application of an efficient semiparametric sufficient dimension reduction estimator. We conduct finite sample numerical simulations to illustrate the performance of our approach, and apply it to a dilated cardiomyopathy study.

引用次数: 0

On the perimeter estimation of pixelated excursion sets of 2D anisotropic random fields 二维各向异性随机场像素化偏移集的周长估计

IF 1 4区数学 Q3 Mathematics

Scandinavian Journal of Statistics

Pub Date : 2023-07-28 DOI: 10.1111/sjos.12682

Ryan Cotsakis, Elena Di Bernardino, T. Opitz

We are interested in creating statistical methods to provide informative summaries of random fields through the geometry of their excursion sets. To this end, we introduce an estimator for the length of the perimeter of excursion sets of random fields on ℝ2 observed over regular square tilings. The proposed estimator acts on the empirically accessible binary digital images of the excursion regions and computes the length of a piecewise linear approximation of the excursion boundary. The estimator is shown to be consistent as the pixel size decreases, without the need of any normalization constant, and with neither assumption of Gaussianity nor isotropy imposed on the underlying random field. In this general framework, even when the domain grows to cover ℝ2, the estimation error is shown to be of smaller order than the side length of the domain. For affine, strongly mixing random fields, this translates to a multivariate Central Limit Theorem for our estimator when multiple levels are considered simultaneously. Finally, we conduct several numerical studies to investigate statistical properties of the proposed estimator in the finite‐sample data setting.This article is protected by copyright. All rights reserved.

我们感兴趣的是创建统计方法，通过其偏移集的几何结构来提供随机场的信息摘要。为此，我们引入了上随机场偏移集周长的一个估计器ℝ2在规则正方形tilings上观察到。所提出的估计器作用于偏移区域的凭经验可访问的二进制数字图像，并计算偏移边界的分段线性近似的长度。随着像素大小的减小，估计器被证明是一致的，不需要任何归一化常数，也不需要对下面的随机场施加高斯性和各向同性的假设。在这个通用框架中，即使域增长到覆盖范围ℝ2，估计误差被显示为比域的边长小的阶数。对于仿射强混合随机场，当同时考虑多个水平时，这转化为我们的估计器的多元中心极限定理。最后，我们进行了几项数值研究，以研究所提出的估计量在有限样本数据集中的统计特性。这篇文章受版权保护。保留所有权利。

{"title":"On the perimeter estimation of pixelated excursion sets of 2D anisotropic random fields","authors":"Ryan Cotsakis, Elena Di Bernardino, T. Opitz","doi":"10.1111/sjos.12682","DOIUrl":"https://doi.org/10.1111/sjos.12682","url":null,"abstract":"We are interested in creating statistical methods to provide informative summaries of random fields through the geometry of their excursion sets. To this end, we introduce an estimator for the length of the perimeter of excursion sets of random fields on ℝ2 observed over regular square tilings. The proposed estimator acts on the empirically accessible binary digital images of the excursion regions and computes the length of a piecewise linear approximation of the excursion boundary. The estimator is shown to be consistent as the pixel size decreases, without the need of any normalization constant, and with neither assumption of Gaussianity nor isotropy imposed on the underlying random field. In this general framework, even when the domain grows to cover ℝ2, the estimation error is shown to be of smaller order than the side length of the domain. For affine, strongly mixing random fields, this translates to a multivariate Central Limit Theorem for our estimator when multiple levels are considered simultaneously. Finally, we conduct several numerical studies to investigate statistical properties of the proposed estimator in the finite‐sample data setting.This article is protected by copyright. All rights reserved.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47849184","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: 4

Statistical Inference for Cox Proportional Hazards Models with a Diverging Number of Covariates. 具有不同数量协变量的 Cox 比例危害模型的统计推断。

IF 0.8 4区数学 Q3 STATISTICS & PROBABILITY

Scandinavian Journal of Statistics

Pub Date : 2023-06-01 Epub Date: 2022-04-25 DOI: 10.1111/sjos.12595

Lu Xia, Bin Nan, Yi Li

For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher information matrix. Such assumptions, however, are often violated under Cox proportion hazards models, leading to biased estimates with under-coverage confidence intervals. We propose a modified debiased lasso method, which solves a series of quadratic programming problems to approximate the inverse information matrix without posing sparse matrix assumptions. We establish asymptotic results for the estimated regression coefficients when the dimension of covariates diverges with the sample size. As demonstrated by extensive simulations, our proposed method provides consistent estimates and confidence intervals with nominal coverage probabilities. The utility of the method is further demonstrated by assessing the effects of genetic markers on patients' overall survival with the Boston Lung Cancer Survival Cohort, a large-scale epidemiology study investigating mechanisms underlying the lung cancer.

对于具有不同数量协变量的回归模型的统计推断，现有文献通常对费雪信息矩阵的逆矩阵做出稀疏性假设。然而，这种假设在 Cox 比例危险模型中经常被违反，从而导致有偏差的估计值和覆盖不足的置信区间。我们提出了一种改进的debiased lasso方法，它可以解决一系列二次编程问题，在不提出稀疏矩阵假设的情况下逼近逆信息矩阵。当协变量的维数随样本量的增加而发散时，我们建立了估计回归系数的渐近结果。大量的模拟证明，我们提出的方法能提供一致的估计值和置信区间，并具有名义覆盖概率。通过波士顿肺癌生存队列（Boston Lung Cancer Survival Cohort）评估遗传标记对患者总生存期的影响，进一步证明了该方法的实用性。

引用次数: 0

首页上一页

1
2
3
4
5
6
7
8
...
10

下一页尾页