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多回归变量线性模型中的残差自助检验AI 解读

This paper is concerned with bootstrap hypothesis testing in linear regression models with many regressors. I show that bootstrap F, LR and LM tests are asymptotically valid even when the numbers of estimated parameters and tested restrictions are not asymptotically negligible fractions of the sample size. One of the conditions for these results is that the regressors come from an asymptotically balanced design. Depending on the number of restrictions tested and on the…

因子Copula模型的结构突变检验AI 解读

We propose new fluctuation tests for detecting structural breaks in factor copula models and analyse the behaviour under the null hypothesis of no change. In the model, the joint copula is given by the copula of random variables which arise from a factor model. This is particularly useful for analysing data with high dimensions. Parameters are estimated with the simulated method of moments (SMM). The discontinuity of the SMM objective function complicates the derivation of a…

分数 Vasicek 模型漂移参数估计的渐近理论AI 解读

This article develops an asymptotic theory for estimators of two parameters in the drift function in the fractional Vasicek model when a continuous record of observations is available. The fractional Vasicek model with long-range dependence is assumed to be driven by a fractional Brownian motion with the Hurst parameter greater than or equal to one half. It is shown that, when the Hurst parameter is known, the asymptotic theory for the persistence parameter depends…

半参数模型的简易迭代 Z 估计量AI 解读

We propose a new iterative estimation algorithm for use in semiparametric models where calculation of Z-estimators by conventional means is difficult or impossible. Unlike a Newton–Raphson approach, which makes use of the entire Hessian, this approach only uses curvature information associated with portions of the Hessian that are relatively easy to calculate. Consistency and asymptotic normality of estimators obtained from this algorithm are established under regularity…

分段局部平稳误差下的自助辅助单位根检验AI 解读

In unit root testing, a piecewise locally stationary process is adopted to accommodate nonstationary errors that can have both smooth and abrupt changes in second- or higher-order properties. Under this framework, the limiting null distributions of the conventional unit root test statistics are derived and shown to contain a number of unknown parameters. To circumvent the difficulty of direct consistent estimation, we propose to use the dependent wild bootstrap to…

含协变量波动率模型的准极大似然推断AI 解读

The asymptotic distribution of the Gaussian quasi-maximum likelihood estimator (QMLE) is obtained for a wide class of asymmetric GARCH models with exogenous covariates. The true value of the parameter is not restricted to belong to the interior of the parameter space, which allows us to derive tests for the significance of the parameters. In particular, the relevance of the exogenous variables can be assessed. The results are obtained without assuming that the innovations…

对 PENCOMP 的讨论AI 解读

We would like to congratulate Zhou, Elliott, and Little (henceforth referred to as ZEL) on an interesting article in an important area of research. ZEL propose a new approach for causal inference u...

用于处理比较的倾向得分惩罚样条方法AI 解读

Valid causal inference from observational studies requires controlling for confounders. When time-dependent confounders are present that serve as mediators of treatment effects and affect future treatment assignment, standard regression methods for controlling for confounders fail. Similar issues also arise in trials with sequential randomization, when randomization at later time points is based on intermediate outcomes from earlier randomized assignments. We propose a…

移动应用激活数据的捕获—再捕获方法AI 解读

This work is concerned with the analysis of marketing data on the activation of applications (apps) on mobile devices. Each application has a hashed identification number that is specific to the device on which it has been installed. This number can be registered by a platform at each activation of the application. Activations on the same device are linked together using the identification number. By focusing on activations that took place at a business location, one can…

考虑发热杀灭寄生虫与测量误差的疟疾归因发热比例估计AI 解读

Malaria is a major health problem in many tropical regions. Fever is a characteristic symptom of malaria. The fraction of fevers that are attributable to malaria, the malaria attributable fever fraction (MAFF), is an important public health measure in that the MAFF can be used to calculate the number of fevers that would be avoided if malaria was eliminated. Despite such causal interpretation, the MAFF has not been considered in the framework of causal inference. We define…

误分类多变量区间删失数据的边际贝叶斯半参数建模AI 解读

Motivated by data gathered in an oral health study, we propose a Bayesian nonparametric approach for population-averaged modeling of correlated time-to-event data, when the responses can only be determined to lie in an interval obtained from a sequence of examination times and the determination of the occurrence of the event is subject to misclassification. The joint model for the true, unobserved time-to-event data is defined semiparametrically; proportional hazards,…

治疗选择下的存活遵从者效应：及时入住重症监护室的应用AI 解读

Pretreatment selection or censoring (“selection on treatment”) can occur when two treatment levels are compared ignoring the third option of neither treatment, in “censoring by death” settings where treatment is only defined for those who survive long enough to receive it, or in general in studies where the treatment is only defined for a subset of the population. Unfortunately, the standard instrumental variable (IV) estimand is not defined in the presence of such…

Group SLOPE：预测变量组的自适应选择AI 解读

Damian Brzyskiab*, Alexej Gossmannc, Weijie Sud & Małgorzata Bogdanea Department of Epidemiology and Biostatistics, Indiana University, Bloomington, INb Institute of Mathematics, Jagiellonian University, Cracow, Polandc Bioinnovation PhD Program, Tulane University, New Orleans, LAd Department of Statistics, University of Pennsylvania, Philadelphia, PAe Institute of Mathematics, University of Wroclaw, Wroclaw, PolandCONTACT Damian Brzyski dbrzyski@iu.edu Department of…

模型误设下的空间相依多重检验及极端气候归因应用AI 解读

The Weather Risk Attribution Forecast (WRAF) is a forecasting tool that uses output from global climate models to make simultaneous attribution statements about whether and how greenhouse gas emissions have contributed to extreme weather across the globe. However, in conducting a large number of simultaneous hypothesis tests, the WRAF is prone to identifying false “discoveries.” A common technique for addressing this multiple testing problem is to adjust the procedure in a…

删失无偏回归树与集成学习AI 解读

This paper proposes a novel paradigm for building regression trees and ensemble learning in survival analysis. Generalizations of the CART and Random Forests algorithms for general loss functions, and in the latter case more general bootstrap procedures, are both introduced. These results, in combination with an extension of the theory of censoring unbiased transformations applicable to loss functions, underpin the development of two new classes of algorithms for…

小角 X 射线散射实验中回转半径的最小均方误差估计AI 解读

Small-angle X-ray scattering (SAXS) is a technique that yields low-resolution structural information of biological macromolecules by exposing a large ensemble of molecules in solution to a powerful X-ray beam. The beam interacts with the molecules and the intensity of the scattered beam is recorded on a detector plate. The radius of gyration for a molecule, which is a measure of the spread of its mass, can be estimated from the lowest scattering angles of SAXS data. This…

FSEM：双胞胎函数型数据的函数型结构方程模型AI 解读

The aim of this paper is to develop a novel class of functional structural equation models (FSEMs) for dissecting functional genetic and environmental effects on twin functional data, while characterizing the varying association between functional data and covariates of interest. We propose a three-stage estimation procedure to estimate varying coefficient functions for various covariates (e.g., gender) as well as three covariance operators for the genetic and environmental…

处理效应变异的分解AI 解读

Understanding and characterizing treatment effect variation in randomized experiments has become essential for going beyond the “black box” of the average treatment effect. Nonetheless, traditional statistical approaches often ignore or assume away such variation. In the context of randomized experiments, this article proposes a framework for decomposing overall treatment effect variation into a systematic component explained by observed covariates and a remaining…

竞争风险子分布的加权非参数极大似然估计AI 解读

Direct regression modeling of the subdistribution has become popular for analyzing data with multiple, competing event types. All general approaches so far are based on non-likelihood based procedures and target covariate effects on the subdistribution. We introduce a novel weighted likelihood function that allows for a direct extension of the Fine-Gray model to a broad class of semiparametric regression models. The model accommodates time-dependent covariate effects on the…

极端依赖类别未知的空间过程建模AI 解读

Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models that exhibit a property known as asymptotic independence. However, weakening dependence does not automatically imply asymptotic independence, and whether the process is truly asymptotically (in)dependent is usually far from clear. The…

大数据线性回归中基于信息的最优子数据选择AI 解读

Extraordinary amounts of data are being produced in many branches of science. Proven statistical methods are no longer applicable with extraordinary large datasets due to computational limitations. A critical step in big data analysis is data reduction. Existing investigations in the context of linear regression focus on subsampling-based methods. However, not only is this approach prone to sampling errors, it also leads to a covariance matrix of the estimators that is…

通过高斯近似高效准确计算 p 值：一种蒙特卡洛方法AI 解读

It is of fundamental interest in statistics to test the significance of a set of covariates. For example, in genome-wide association studies, a joint null hypothesis of no genetic effect is tested for a set of multiple genetic variants. The minimum p-value method, higher criticism, and Berk–Jones tests are particularly effective when the covariates with nonzero effects are sparse. However, the correlations among covariates and the nonGaussian distribution of the response…

多元函数型数据的部分线性函数型可加模型AI 解读

Raymond K. W. Wonga, Yehua Lib* http://orcid.org/0000-0002-5945-378X & Zhengyuan Zhuca Department of Statistics, Texas A&M University, College Station, TXb Department of Statistics, University of California, Riverside, CAc Department of Statistics & Statistical Laboratory, Iowa State University, Ames, IACONTACT Yehua Li yehuali@ucr.edu Department of Statistics, University of California, Riverside, CA 92521Color versions of one or more of the figures in the article can be…

逻辑回归与一般指数模型的稳健变量及交互项选择AI 解读

Under the logistic regression framework, we propose a forward-backward method, SODA, for variable selection with both main and quadratic interaction terms. In the forward stage, SODA adds in predictors that have significant overall effects, whereas in the backward stage SODA removes unimportant terms to optimize the extended Bayesian Information Criterion (EBIC). Compared with existing methods for variable selection in quadratic discriminant analysis, SODA can deal with…