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关系数据矩阵中的节点依赖检验AI 解读

Relational data are often represented as a square matrix, the entries of which record the relationships between pairs of objects. Many statistical methods for the analysis of such data assume some degree of similarity or dependence between objects in terms of the way they relate to each other. However, formal tests for such dependence have not been developed. We provide a test for such dependence using the framework of the matrix normal model, a type of multivariate normal…

大量相关正态变量的经验分布AI 解读

Motivated by the advent of high dimensional highly correlated data, this work studies the limit behavior of the empirical cumulative distribution function (ecdf) of standard normal random variables under arbitrary correlation. First, we provide a necessary and sufficient condition for convergence of the ecdf to the standard normal distribution. Next, under general correlation, we show that the ecdf limit is a random, possible infinite, mixture of normal distribution…

多元时间序列变化检测及其脑电数据应用AI 解读

The primary contributions of this article are rigorously developed novel statistical methods for detecting change points in multivariate time series. We extend the class of score type change point statistics considered in 2007 by Hušková, Prášková, and Steinebach to the vector autoregressive (VAR) case and the epidemic change alternative. Our proposed procedures do not require the observed time series to actually follow the VAR model. Instead, following the strategy…

边际结构模型中逆概率权重的稳健估计AI 解读

Marginal structural models (MSMs) are becoming increasingly popular as a tool for causal inference from longitudinal data. Unlike standard regression models, MSMs can adjust for time-dependent observed confounders while avoiding the bias due to the direct adjustment for covariates affected by the treatment. Despite their theoretical appeal, a main practical difficulty of MSMs is the required estimation of inverse probability weights. Previous studies have found that MSMs can…

含结构突变的多区制门限自回归模型估计AI 解读

The threshold autoregressive (TAR) model is a class of nonlinear time series models that have been widely used in many areas. Due to its nonlinear nature, one major difficulty in fitting a TAR model is the estimation of the thresholds. As a first contribution, this article develops an automatic procedure to estimate the number and values of the thresholds, as well as the corresponding AR order and parameter values in each regime. These parameter estimates are defined as the…

偏差缩减的双重稳健估计AI 解读

Over the past decade, doubly robust estimators have been proposed for a variety of target parameters in causal inference and missing data models. These are asymptotically unbiased when at least one of two nuisance working models is correctly specified, regardless of which. While their asymptotic distribution is not affected by the choice of root-n consistent estimators of the nuisance parameters indexing these working models when all working models are correctly specified,…

稀疏纵向协变量下的比例风险模型分析AI 解读

Regression analysis of censored failure observations via the proportional hazards model permits time-varying covariates which are observed at death times. In practice, such longitudinal covariates are typically sparse and only measured at infrequent and irregularly spaced follow-up times. Full likelihood analyses of joint models for longitudinal and survival data impose stringent modelling assumptions which are difficult to verify in practice and which are complicated both…

高维协方差矩阵估计的带宽选择AI 解读

Yumou Qiu & Song Xi ChenYumou Qiu is Assistant Professor, Department of Statistics, University of Nebraska-Lincoln, NE 68583-0963 (E-mail: ). Song Xi Chen is Chair Professor, Department of Business Statistics and Econometrics, Guanghua School of Management and Center for Statistical Science, Peking University, Beijing 100651, China, and Professor, Department of Statistics, Iowa State University, Ames, IA 50011-1210 (E-mail: ).We thank the editors, the AE and three anonymous…

半参数优势比模型的似然推断AI 解读

A flexible semiparametric odds ratio model has been proposed to unify and to extend both the log-linear model and the joint normal model for data with a mix of discrete and continuous variables. The semiparametric odds ratio model is particularly useful for analyzing biased sampling designs. However, statistical inference of the model has not been systematically studied when more than one nonparametric component is involved in the model. In this article, we study the maximum…

序贯回归多重插补算法的收敛性质AI 解读

A sequential regression or chained equations imputation approach uses a Gibbs sampling-type iterative algorithm that imputes the missing values using a sequence of conditional regression models. It is a flexible approach for handling different types of variables and complex data structures. Many simulation studies have shown that the multiple imputation inferences based on this procedure have desirable repeated sampling properties. However, a theoretical weakness of this…

E-MS 算法：不完整数据下的模型选择AI 解读

We propose a procedure associated with the idea of the E-M algorithm for model selection in the presence of missing data. The idea extends the concept of parameters to include both the model and the parameters under the model, and thus allows the model to be part of the E-M iterations. We develop the procedure, known as the E-MS algorithm, under the assumption that the class of candidate models is finite. Some special cases of the procedure are considered, including E-MS…

离散参数空间先验概率质量函数的客观构造方法AI 解读

C. Villa & S. G. WalkerC. Villa is Lecturer, School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, UK (E-mail: cv88@kent.ac.uk). S. G. Walker is Professor, Department of Statistics and Data Sciences, and Division of Statistics and Scientific Computation, University of Texas at Austin, TX 78712 (E-mail: s.g.walker@math.utexas.edu).Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/r/jasa.We…

基于偏微分方程惩罚空间回归的血流速度场估计AI 解读

We propose an innovative method for the accurate estimation of surfaces and spatial fields when prior knowledge of the phenomenon under study is available. The prior knowledge included in the model derives from physics, physiology, or mechanics of the problem at hand, and is formalized in terms of a partial differential equation governing the phenomenon behavior, as well as conditions that the phenomenon has to satisfy at the boundary of the problem domain. The proposed…

含移动平均残差的非线性自回归模型的 Whittle 似然估计AI 解读

The Whittle likelihood estimation (WLE) has played a fundamental role in the development of both theory and computation of time series analysis. However, WLE is only applicable to models whose theoretical spectral density function (SDF) is known up to the parameters in the models. In this article, we propose a residual-based WLE, called extended WLE (XWLE), which can estimate models with their SDFs only partially available, including many popular time series models with…

函数型主成分分析的 S 估计量AI 解读

Principal component analysis is a widely used technique that provides an optimal lower-dimensional approximation to multivariate or functional datasets. These approximations can be very useful in identifying potential outliers among high-dimensional or functional observations. In this article, we propose a new class of estimators for principal components based on robust scale estimators. For a fixed dimension q, we robustly estimate the q-dimensional linear space that…

多来源数据的半参数贝叶斯密度估计：全球儿童营养不足荟萃分析AI 解读

Undernutrition, resulting in restricted growth, and quantified here using height-for-age z-scores, is an important contributor to childhood morbidity and mortality. Since all levels of mild, moderate, and severe undernutrition are of clinical and public health importance, it is of interest to estimate the shape of the z-scores’ distributions. We present a finite normal mixture model that uses data on 4.3 million children to make annual country-specific estimates of these…

统一振幅与相位分析：普通话函数型多变量混合效应的组成数据方法AI 解读

Mandarin Chinese is characterized by being a tonal language; the pitch (or F0) of its utterances carries considerable linguistic information. However, speech samples from different individuals are subject to changes in amplitude and phase, which must be accounted for in any analysis that attempts to provide a linguistically meaningful description of the language. A joint model for amplitude, phase, and duration is presented, which combines elements from functional data…

用于灵长类认知研究的二项与秩数据联合贝叶斯建模AI 解读

In recent years, substantial effort has been devoted to methods for analyzing data containing mixed response types, but such techniques typically do not include rank data among the response types. Some unique challenges exist in analyzing rank data, particularly when ties are prevalent. We present techniques for jointly modeling binomial and rank data using Bayesian latent variable models. We apply these techniques to compare the cognitive abilities of nonhuman primates…

High-throughput DNA sequencing allows for the genotyping of common and rare variants for genetic association studies. At the present time and for the foreseeable future, it is not economically feasible to sequence all individuals in a large cohort. A cost-effective strategy is to sequence those individuals with extreme values of a quantitative trait. We consider the design under which the sampling depends on multiple quantitative traits. Under such trait-dependent sampling,…

研究内样本协方差矩阵部分缺失时的多元元回归贝叶斯推断AI 解读

Multivariate meta-regression models are commonly used in settings where the response variable is naturally multidimensional. Such settings are common in cardiovascular and diabetes studies where the goal is to study cholesterol levels once a certain medication is given. In this setting, the natural multivariate endpoint is low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). In this article, we…

新外科医生健康结局观察研究中的精细协变量平衡与大规模稀疏最优匹配AI 解读

Every newly trained surgeon performs her first unsupervised operation. How do the health outcomes of her patients compare with the patients of experienced surgeons? Using data from 498 hospitals, we compare 1252 pairs comprised of a new surgeon and an experienced surgeon working at the same hospital. We introduce a new form of matching that matches patients of each new surgeon to patients of an otherwise similar experienced surgeon at the same hospital, perfectly balancing…

含空间相关随机效应的火炬松生存分析AI 解读

Loblolly pine, a native pine species of the southeastern United States, is the most-planted species for commercial timber. Predicting survival of loblolly pine following planting is of great interest to researchers in forestry science as it is closely related to the yield of timber. Data were collected from a region-wide thinning study, where permanent plots, located at 182 sites ranging from central Texas east to Florida and north to Delaware, were established in 1980–1981.…

We propose small-variance asymptotic approximations for inference on tumor heterogeneity (TH) using next-generation sequencing data. Understanding TH is an important and open research problem in biology. The lack of appropriate statistical inference is a critical gap in existing methods that the proposed approach aims to fill. We build on a hierarchical model with an exponential family likelihood and a feature allocation prior. The proposed implementation of posterior…

错误发现率回归及初级视觉皮层神经同步检测应用AI 解读

Many approaches for multiple testing begin with the assumption that all tests in a given study should be combined into a global false-discovery-rate analysis. But this may be inappropriate for many of today's large-scale screening problems, where auxiliary information about each test is often available, and where a combined analysis can lead to poorly calibrated error rates within different subsets of the experiment. To address this issue, we introduce an approach called…