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群组随机试验分析的最优置换检验AI 解读

Two facts complicate the comparison of interventions in group randomized trials (GRT's), a family of clinical trials in which each member of a particular group receives the same treatment assignment. First, individual outcomes within each group are often correlated. Second, the number of groups in a GRT is often not sufficient to make asymptotic approximations possible. Therefore, the tests used with methods, such as generalized estimating equations (GEE) and penalized quasi…

夹心协方差矩阵估计效率的一则札记AI 解读

The sandwich estimator, also known as robust covariance matrix estimator, heteroscedasticity-consistent covariance matrix estimate, or empirical covariance matrix estimator, has achieved increasing use in the econometric literature as well as with the growing popularity of generalized estimating equations. Its virtue is that it provides consistent estimates of the covariance matrix for parameter estimates even when the fitted parametric model fails to hold or is not even…

非凹惩罚似然变量选择及其 Oracle 性质AI 解读

Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized likelihood approaches are proposed to handle these kinds of problems. The proposed methods select variables and estimate coefficients simultaneously. Hence they enable us to…

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检测非线性个体曲线急剧变化的贝叶斯模型AI 解读

We propose a model for longitudinal data with random effects that includes model-based smoothing of measurements over time. This research is motivated by experiments evaluating the hemodynamic effects of various agents in tumor-bearing rats. In one set of experiments, the rats breathed room air, followed by carbogen (a mixture of pure oxygen and carbon dioxide). The experimental responses are longitudinal measurements of oxygen pressure measured in tissue, tumor blood flow,…

利用MCMC对时间相关数据进行多元受体建模AI 解读

Multivariate receptor modeling aims to estimate pollution source profiles and the amounts of pollution based on a series of ambient concentrations of multiple chemical species over time. Air pollution data often show temporal dependence due to meteorology and/or background sources. Previous approaches to receptor modeling do not incorporate this dependence. We model dependence in the data using a time series approach so that we can incorporate extra sources of variability in…

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多期控制的贝叶斯启发式方法AI 解读

In multiperiod control problems, one needs to sequentially choose the value of a set of multiple input variables, xn, to keep the value of a single output variable, yn, close to a target, T. At any stage n, the selection of xn poses a difficult dilemma. On the one hand, xn has to be such that (yn(xn) - T)2 is small in expectation. On the other hand, xn has to be such that it maximizes the amount of information in yn(xn) about the model relating yn and xn, to help keep the…

切片逆回归的扩展AI 解读

Sliced inverse regression (SIR) and an associated chi-squared test for dimension have been introduced as a method for reducing the dimension of regression problems whose predictor variables are normal. In this article the assumptions on the predictor distribution, under which the chi-squared test was proved to apply, are relaxed, and the result is extended. A general weighted chi-squared test that does not require normal regressors for the dimension of a regression is given.…

小波逼近的正则化AI 解读

In this paper, we introduce nonlinear regularized wavelet estimators for estimating nonparametric regression functions when sampling points are not uniformly spaced. The approach can apply readily to many other statistical contexts. Various new penalty functions are proposed. The hard-thresholding and soft-thresholding estimators of Donoho and Johnstone are specific members of nonlinear regularized wavelet estimators. They correspond to the lower and upper envelopes of a…

计算 Bayes 因子的马尔可夫链蒙特卡洛方法AI 解读

The problem of calculating posterior probabilities for a collection of competing models and associated Bayes factors continues to be a formidable challenge for applied Bayesian statisticians. Current approaches that take advantage of modern Markov chain Monte Carlo computing methods include those that attempt to sample over some form of the joint space created by the model indicators and the parameters for each model, others that sample over the model space alone, and still…

聚类二元与连续响应联合建模的相关Probit模型AI 解读

A difficulty in joint modeling of continuous and discrete response variables is the lack of a natural multivariate distribution. For joint modeling of clustered observations on binary and continuous responses, we study a correlated probit model that has an underlying normal latent variable for the binary responses. Catalano and Ryan have factored the model into a marginal and a conditional component and used generalized estimating equations methodology to estimate the…

不假定参数化误差分布的 Box–Cox 变换模型估计AI 解读

Box and Cox proposed a power transformation for the response variable that yields a linear regression model with normal error and constant variance. Inference procedures for the regression coefficients and transformation parameter under this model setting have been studied extensively. In this article we propose a simple semiparametric estimation method for the Box–Cox transformation model with no specific parametric assumption on the distribution of the error term. The…

随机块结构的估计与预测AI 解读

A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is proposed. The probability model assumes that the vertices of the digraph are partitioned into several unobserved (latent) classes and that the probability distribution of the relation between two vertices depends only on the classes to which they belong. A Bayesian estimator based on Gibbs sampling is proposed. The basic model is not identified, because class labels are arbitrary. The…

检验可能存在依赖的过程是否不相关AI 解读

An analysis is presented of a new testing procedure for the null hypothesis that a stochastic process is uncorrelated when the process is possibly dependent. Unlike with existing procedures, the user does not need to choose any arbitrary number to implement the proposed test. The asymptotic null distribution of the proposed test statistic is not standard, but it is tabulated by means of simulations. The test is compared with two alternative test procedures that require…

利用广义估计方程进行聚类数据的半参数回归AI 解读

We consider estimation in a semiparametric generalized linear model for clustered data using estimating equations. Our results apply to the case where the number of observations per cluster is finite, whereas the number of clusters is large. The mean of the outcome variable μ is of the form g(μ) = XTβ + θ(T), where g(·) is a link function, X and T are covariates, β is an unknown parameter vector, and θ(t) is an unknown smooth function. Kernel estimating equations proposed…

Multidimensional scaling is widely used to handle data that consist of similarity or dissimilarity measures between pairs of objects. We deal with two major problems in metric multidimensional scaling–configuration of objects and determination of the dimension of object configuration–within a Bayesian framework. A Markov chain Monte Carlo algorithm is proposed for object configuration, along with a simple Bayesian criterion, called MDSIC, for choosing their dimension.…

Digital deconvolution concerns the restoration of an underlying discrete signal from a blurred noisy observation sequence. The problem can be formulated in a Bayesian framework. As is usual in the Bayesian context, the computation of relevant posterior quantities is the major challenge. Previous work made substantial progress toward making this computation feasible, most notably through the Gibbs sampling approach of Chen and Li and the sequential importance sampling…

协变量测量误差的局部辅助拟得分模型AI 解读

We use the notion of locally ancillary estimating functions to develop a quasi-score method for fitting regression models containing measurement error in the covariates. Suppose that interest is on the model E(Y|u, w) for response Y, the observed data are (y, x, w), and X is a mismeasured surrogate for u. We take a functional modeling approach, treating the u as a fixed nuisance parameter. Beginning with quasi-scores for the regression parameter and the unknown u, we derive…

混合自回归条件异方差模型AI 解读

We propose a mixture autoregressive conditional heteroscedastic (MAR-ARCH) model for modeling nonlinear time series. The models consist of a mixture of K autoregressive components with autoregressive conditional heteroscedasticity; that is, the conditional mean of the process variable follows a mixture AR (MAR) process, whereas the conditional variance of the process variable follows a mixture ARCH process. In addition to the advantage of better description of the…

随机神经网络及其在非线性时间序列中的应用AI 解读

We consider a variant of the conventional neural network model, called the stochastic neural network, that can be used to approximate complex nonlinear stochastic systems. We show how the expectation-maximization algorithm can be used to develop efficient estimation schemes that have much lower computational complexity than those for conventional neural networks. This enables us to carry out model selection procedures, such as the Bayesian information criterion, to choose…

弓头鲸胎儿生长与妊娠期的估计AI 解读

We address estimating fetal growth and gestation for bowhead whales of the Bering, Chukchi, and Beaufort seas stock. This population is subject to a subsistence hunt by Eskimo whale hunters, which is monitored via a quota system established by the International Whaling Commission. Quota determination is assisted by biological information, such as fetal growth and gestation, which is the basis of a population dynamics model used to estimate the annual replacement yield of the…

多项重复测量与双变量事件时间联合分析的潜变量模型AI 解读

This article presents a novel approach to analyzing a complex dataset from a prevention trial, where outcomes comprise multiple repeated mental health items and times to initiation of alcohol and tobacco use. The dataset has a nonnegligible portion of missing values and interval or left censored events. The substantive interest of the trial suggests a psychiatric distress latent variable that is reflected in the mental health items and potentially affects initiation of…

纵向数据与事件时间数据的联合建模：艾滋病应用AI 解读

In many clinical and epidemiologic studies, periodically measured disease markers are used to monitor progression to the onset of disease. Motivated by a study of CD4 counts in men infected with human immunodeficiency virus (HIV) at risk for acquired immunodeficiency syndrome (AIDS), we developed a joint model for analysis of both longitudinal and event time data. We use a longitudinal model for continuous data that incorporates a mean structure dependent on covariates, a…