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有序边际二维列联表中的正象限依赖与边际建模AI 解读

For a collection of two-way tables, where subjects are cross-classified according to the same pair of ordinal categorical variables conditionally on the value of one or more discrete explanatory variables, we propose a general approach to likelihood inference that combines marginal modeling with fitting and testing of inequality constraints such as those implied by the assumption that one marginal distribution is stochastically larger than the other, positive dependence and…

协变量含测量误差的逻辑回归一致性函数方法AI 解读

We propose consistent functional methods for logistic regression in which some covariates are not accurately ascertainable. Among existing methods for generalized linear models, the conditional-score approach to normal errors does not guarantee the convergence of its estimators, and the corrected-score method generally is not applicable to the logistic-regression score function. In this article, after constructing a correction-amenable estimation procedure with the true…

贝叶斯半参数中位数回归建模AI 解读

Median regression models become an attractive alternative to mean regression models when employing flexible families of distributions for the errors. Classical approaches are typically algorithmic with desirable properties emerging asymptotically. However, nonparametric error models may be most attractive in the case of smaller sample sizes where parametric specifications are difficult to justify. Hence, a Bayesian approach, enabling exact inference given the observed data,…

空间相关数据的客观贝叶斯分析AI 解读

Spatially varying phenomena are often modeled using Gaussian random fields, specified by their mean function and covariance function. The spatial correlation structure of these models is commonly specified to be of a certain form (e.g., spherical, power exponential, rational quadratic, or Matérn) with a small number of unknown parameters. We consider objective Bayesian analysis of such spatial models, when the mean function of the Gaussian random field is specified as in a…

加性回归中的结构检验AI 解读

We consider the component analysis problem for a regression model with an additive structure. The problem is to test whether some of the additive components are of polynomial structure (e.g., linear) without specifying the structure of the remaining components. A particular case is the problem of selecting the significant covariates. The method that we present is based on the wavelet transform using the Haar basis, which allows for applications under mild conditions on the…

微阵列实验的经验贝叶斯分析AI 解读

Microarrays are a novel technology that facilitates the simultaneous measurement of thousands of gene expression levels. A typical microarray experiment can produce millions of data points, raising serious problems of data reduction, and simultaneous inference. We consider one such experiment in which oligonucleotide arrays were employed to assess the genetic effects of ionizing radiation on seven thousand human genes. A simple nonparametric empirical Bayes model is…

复发事件数据的非参数估计AI 解读

The problem of nonparametric estimation for the distribution function governing the time to occurrence of a recurrent event in the presence of censoring is considered. We derive Nelson–Aalen and Kaplan–Meier-type estimators for the distribution function, and establish their respective finite-sample and asymptotic properties. We allow for random observation periods for each subject under study and explicitly account for the informative sum-quota nature of the data accrual…

半参数非线性混合效应模型及其应用AI 解读

Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model variation within each subject and some fixed and/or random parameters to model variation between subjects. The parametric NLMM may be too restrictive, and the semiparametric SEMOR model ignores correlations within each subject. In this article we propose a class of semiparametric…

物种组成的统计解释AI 解读

The relative abundance of different species characterizes the structure of a biological community. We analyze an experiment addressing the relationship between omnivorous feeding linkages and community stability. Our goal is to determine whether communities with different predator compositions respond similarly to environmental disturbance. To evaluate these data, we develop a hierarchical statistical model that combines Aitchison's logistic normal distribution with a…

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,…

根接近一的趋势时间序列之似然推断AI 解读

This paper studies likelihood-based estimation and tests for autoregressive time series models with deterministic trends and general disturbance distributions. In particular, a joint estimation of the trend coefficients and the autoregressive parameter is considered. Asymptotic analysis on the M -estimators is provided. It is shown that the limiting distributions of these estimators involve nonlinear equation systems of Brownian motions even for the simple case of least…

利用小波进行 ARCH 效应的单侧检验AI 解读

There has been increasing interest recently in hypothesis testing with inequality restrictions. An important example in time series econometrics is hypotheses on autoregressive conditional heteroskedasticity (ARCH). We propose a one-sided test for ARCH effects using a wavelet spectral density estimator at frequency zero of a squared regression residual series. The square of an ARCH process is positively correlated at all lags, resulting in a spectral mode at frequency zero.…

通过部分 Lq 范数估计加性非参数模型：分数阶的代价AI 解读

We propose a new method for estimating additive nonparametric regression models based on taking the L q median of a sample of kernel estimators. We establish the consistency and asymptotic normality of our procedures. The rate of convergence depends on the value of q . For q > 3/2 one has the usual one-dimensional rate, but if q ≤ 3/2 the rate can be slower.

选择性偏差的局部敏感性近似AI 解读

Summary Observational data analysis is often based on tacit assumptions of ignorability or randomness. The paper develops a general approach to local sensitivity analysis for selectivity bias, which aims to study the sensitivity of inference to small departures from such assumptions. If M is a model assuming ignorability, we surround M by a small neighbourhood N defined in the sense of Kullback–Leibler divergence and then compare the inference for models in N with that for…

利用协变量可靠性样本的失效时间回归风险集校准法AI 解读

Summary Regression parameter estimation in the Cox failure time model is considered when regression variables are subject to measurement error. Assuming that repeat regression vector measurements adhere to a classical measurement model, we can consider an ordinary regression calibration approach in which the unobserved covariates are replaced by an estimate of their conditional expectation given available covariate measurements. However, since the rate of withdrawal from the…

响应偏倚抽样下的参数模型AI 解读

Summary Suppose that subjects in a population follow the model f(y*|x*;θ) where y* denotes a response, x* denotes a vector of covariates and θ is the parameter to be estimated. We consider response-biased sampling, in which a subject is observed with a probability which is a function of its response. Such response-biased sampling frequently occurs in econometrics, epidemiology and survey sampling. The semiparametric maximum likelihood estimate of θ is derived, along with its…

利用已实现效应的信息界定前瞻性因果效应AI 解读

Summary The potential outcomes approach to causal inference postulates that each individual has a number of possibly latent outcomes, each of which would be observed under a different treatment. For any individual, some of these outcomes will be unobservable or counterfactual. Information about post-treatment characteristics sometimes allows statements about what would have happened if an individual or group with these characteristics had received a different treatment.…

模型误设对 Cox 比例风险模型中无随机治疗效应检验的影响AI 解读

Summary We examine the asymptotic and small sample properties of model-based and robust tests of the null hypothesis of no randomized treatment effect based on the partial likelihood arising from an arbitrarily misspecified Cox proportional hazards model. When the distribution of the censoring variable is either conditionally independent of the treatment group given covariates or conditionally independent of covariates given the treatment group, the numerators of the partial…

提高非参数预测区间的覆盖准确性AI 解读

Summary Methods are suggested for improving the coverage accuracy of intervals for predicting future values of a random variable drawn from a sampled distribution. It is shown that properties of solutions to such problems may be quite unexpected. For example, the bootstrap and the jackknife perform very poorly when used to calibrate coverage, although the jackknife estimator of the true coverage is virtually unbiased. A version of the smoothed bootstrap can be employed for…

异质群体中的流行病：基本再生数与安全疫苗覆盖率估计AI 解读

Summary A stochastic multitype model for the spread of an infectious disease in a community of heterogeneous individuals is analysed. In particular, estimates of R 0 (the basic reproduction number) and the critical vaccination coverage are derived, where estimation is based on final size data of an outbreak in the community. It is shown that these key parameters cannot be estimated consistently from data; only upper and lower bounds can be estimated. Confidence regions for…