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用于发现基因调控网络的回归混合模型变量选择AI 解读

The profusion of genomic data through genome sequencing and gene expression microarray technology has facilitated statistical research in determining gene interactions regulating a biological process. Current methods generally consist of a two-stage procedure: clustering gene expression measurements and searching for regulatory “switches,” typically short, conserved sequence patterns (motifs) in the DNA sequence adjacent to the genes. This process often leads to misleading…

营养流行病学中的结构化测量误差AI 解读

Preterm birth, defined as delivery before 37 completed weeks' gestation, is a leading cause of infant morbidity and mortality. Identifying factors related to preterm delivery is an important goal of public health professionals who wish to identify etiologic pathways to target for prevention. Validation studies are often conducted in nutritional epidemiology in order to study measurement error in instruments that are generally less invasive or less expensive than "gold…

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不规则观测下谱密度的半参数估计AI 解读

We propose a semiparametric method for estimating spectral densities of isotropic Gaussian processes with scattered data. The spectral density function (Fourier transform of the covariance function) is modeled as a linear combination of B-splines up to a cutoff frequency and, from this point, a truncated algebraic tail. We calculate an analytic expression for the covariance function and tackle several numerical issues that arise when calculating the likelihood. The…

时空协方差函数性质的非参数检验AI 解读

We propose a unified framework for testing various assumptions commonly made for covariance functions of stationary spatio-temporal random fields. The methodology is based on the asymptotic normality of space–time covariance estimators. We focus on tests for full symmetry and separability in this article, but our framework naturally covers testing for isotropy and Taylor's hypothesis. Our test successfully detects the asymmetric and nonseparable features in two sets of wind…

大规模多重比较中的零分布与非零效应比例估计AI 解读

An important issue raised by Efron in the context of large-scale multiple comparisons is that in many applications, the usual assumption that the null distribution is known is incorrect, and seemingly negligible differences in the null may result in large differences in subsequent studies. This suggests that a careful study of estimation of the null is indispensable. In this article we consider the problem of estimating a null normal distribution, and a closely related…

有限总体总量的稳健模型预测与模型辅助预测AI 解读

The prediction approach to finite population inference has received considerable attention in recent years. Under this approach, the finite population is assumed to be a realization from a superpopulation described by a known probability model, usually a linear model. The prediction approach is often criticized for its lack of robustness against model misspecification. In this article we revisit this important issue and introduce a new robust prediction approach in which the…

局部多项式回归的平滑位置依赖带宽选择AI 解读

A bandwidth function for local polynomial models is commonly obtained by optimizing a pointwise penalty criterion, such as an estimated mean squared error (MSE), over a grid of predictor locations. A resultant regression estimate may suffer from irregularities, such as discontinuities, and contextual information over nearby predictor locations is not used. To mediate these difficulties, ad hoc postprocessing is sometimes carried out in the form of smoothing of the penalty…

广义加性模型辅助的森林资源估计AI 解读

Multiphase surveys are often conducted in forest inventories, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from remote sensing. The relationship between the ground visit measurements and the remote sensing variables is…

带权观测的扫描统计量AI 解读

We examine scan statistics for one-dimensional marked Poisson processes. Such statistics tabulate the maximum weighted count of event occurrences within a window of predetermined width over all windows within an observed interval. We derive analytical formulas and also give an importance sampling method for approximating the tail probabilities of scan statistics. Because high-throughput genomic sequencing has led to the availability of massive amounts of biomolecular…

L1范数多分类支持向量机AI 解读

Binary support vector machines (SVMs) have been proven to deliver high performance. In multiclass classification, however, issues remain with respect to variable selection. One challenging issue is classification and variable selection in the presence of variables in the magnitude of thousands, greatly exceeding the size of training sample. This often occurs in genomics classification. To meet the challenge, this article proposes a novel multiclass support vector machine,…

多变量生存数据的部分线性风险回归AI 解读

This article studies estimation of partially linear hazard regression models for multivariate survival data. A profile pseudo–partial likelihood estimation method is proposed under the marginal hazard model framework. The estimation on the parameters for the linear part is accomplished by maximization of a pseudo–partial likelihood profiled over the nonparametric part. This enables us to obtain -consistent estimators of the parametric component. Asymptotic normality is…

一般动态因子模型中的因子数量确定AI 解读

This article develops an information criterion for determining the number q of common shocks in the general dynamic factor model developed by Forni et al., as opposed to the restricted dynamic model considered by Bai and Ng and by Amengual and Watson. Our criterion is based on the fact that this number q is also the number of diverging eigenvalues of the spectral density matrix of the observations as the number n of series goes to infinity. We provide sufficient conditions…

空间贝叶斯变量选择及其在功能磁共振成像中的应用AI 解读

We propose a procedure to undertake Bayesian variable selection and model averaging for a series of regressions located on a lattice. For those regressors that are in common in the regressions, we consider using an Ising prior to smooth spatially the indicator variables representing whether or not the variable is zero or nonzero in each regression. This smooths spatially the probabilities that each independent variable is nonzero in each regression and indirectly smooths…

跳跃曲面估计、边缘检测与图像恢复AI 解读

Surface estimation is important in many applications. When conventional smoothing procedures (e.g., running averages, local polynomial kernel smoothing procedures, smoothing spline procedures) are used for estimating jump surfaces from noisy data, jumps are blurred at the same time when noise is removed. In recent years, new smoothing methodologies have been proposed in the statistical literature for detecting jumps in surfaces and for estimating jump surfaces with jumps…

纵向数据变系数模型的经验似然推断AI 解读

In this article local empirical likelihood-based inference for a varying coefficient model with longitudinal data is investigated. First, we show that the naive empirical likelihood ratio is asymptotically standard chi-squared when undersmoothing is employed. The ratio is self-scale invariant and the plug-in estimate of the limiting variance is not needed. Second, to enhance the performance of the ratio, mean-corrected and residual-adjusted empirical likelihood ratios are…

波动率估计中时间域与状态域方法的动态整合AI 解读

Time- and state-domain methods are two common approaches to nonparametric prediction. Whereas the former uses data predominantly from recent history, the latter relies mainly on historical information. Combining these two pieces of valuable information is an interesting challenge in statistics. We surmount this problem by dynamically integrating information from both the time and state domains. The estimators from these two domains are optimally combined based on a…

利用删失回归模型评估 t 年生存者预测规则AI 解读

Suppose that we are interested in establishing simple but reliable rules for predicting future t-year survivors through censored regression models. In this article we present inference procedures for evaluating such binary classification rules based on various prediction precision measures quantified by the overall misclassification rate, sensitivity and specificity, and positive and negative predictive values. Specifically, under various working models, we derive consistent…

随机化后所选子群中生存结局比较的敏感性分析AI 解读

In some randomized studies, researchers are interested in determining the effect of treatment assignment on outcomes that may exist only in a subset chosen after randomization. For example, in preventative human immunodeficiency virus (HIV) vaccine efficacy trials, it is of interest to determine whether randomization to vaccine affects postinfection outcomes that may be right-censored. Such outcomes in these trials include time from infection diagnosis to initiation of…

协方差函数半参数估计下的纵向数据分析AI 解读

Improving efficiency for regression coefficients and predicting trajectories of individuals are two important aspects in analysis of longitudinal data. Both involve estimation of the covariance function. Yet, challenges arise in estimating the covariance function of longitudinal data collected at irregular time points. A class of semiparametric models for the covariance function is proposed by imposing a parametric correlation structure while allowing a nonparametric…

约束统计推断中的高维小样本视角AI 解读

High-dimensional categorical data models, often with inadequately large sample sizes, crop up in many fields of application. The SARS epidemic, originating in southern China in 2002, had an identified single-stranded and positive-sense RNA virus with large genome size and moderate mutation rate. The present genomic study is used as a prime illustration for motivating appropriate statistical methodology for comprehending the genomic variation in such high-dimensional…

方向统计与形状分析中多样本问题的枢轴自助法AI 解读

We propose a novel bootstrap hypothesis testing approach for the problem of testing a null hypothesis of a common mean direction, mean polar axis, or mean shape across several populations of real unit vectors (the directional case) or complex unit vectors (the two-dimensional shape case). Multisample testing problems of this type arise frequently in directional statistics and shape analysis (as in other areas of statistics), but to date there has been relatively little…

奇异值分解的模型平均与维度选择AI 解读

Many multivariate data-analysis techniques for an m × n matrix Y are related to the model Y = M + E, where Y is an m × n matrix of full rank and M is an unobserved mean matrix of rank K < (m ∧ n). Typically the rank of M is estimated in a heuristic way and then the least-squares estimate of M is obtained via the singular value decomposition of Y, yielding an estimate that can have a very high variance. In this article we suggest a model-based alternative to the preceding…