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区域判定问题AI 解读

In the problem of regions, we wish to know which one of a discrete set of possibilities applies to a continuous parameter vector. This problem arises in the following way: we compute a descriptive statistic from a set of data, notice an interesting feature and wish to assign a confidence level to that feature. For example, we compute a density estimate and notice that the estimate is bimodal. What confidence can we assign to bimodality? A natural way to measure confidence is…

基于固定平滑参数核密度估计量的拟合优度检验AI 解读

In this paper, we study the bias-corrected test developed in Fan (1994). It is based on the integrated squared difference between a kernel estimator of the unknown density function of a random vector and a kernel smoothed estimator of the parametric density function to be tested under the null hypothesis. We provide an alternative asymptotic approximation of the finite-sample distribution of this test by fixing the smoothing parameter. In contrast to the normal approximation…

多元失效时间数据的边际回归模型AI 解读

In this article we propose a general Cox-type regression model to formulate the marginal distributions of multivariate failure time data. This model has a nested structure in that it allows different baseline hazard functions among distinct failure types and imposes a common baseline hazard function on the failure times of the same type. We prove that the maximum “quasi-partial-likelihood” estimator for the vector of regression parameters under the independence working…

嵌套与交叉曲线样本分析的平滑样条模型AI 解读

We introduce a class of models for an additive decomposition of groups of curves stratified by crossed and nested factors, generalizing smoothing splines to such samples by associating them with a corresponding mixed-effects model. The models are also useful for imputation of missing data and exploratory analysis of variance. We prove that the best linear unbiased predictors (BLUPs) from the extended mixed-effects model correspond to solutions of a generalized penalized…

动态系统的序贯蒙特卡洛方法AI 解读

We provide a general framework for using Monte Carlo methods in dynamic systems and discuss its wide applications. Under this framework, several currently available techniques are studied and generalized to accommodate more complex features. All of these methods are partial combinations of three ingredients: importance sampling and resampling, rejection sampling, and Markov chain iterations. We provide guidelines on how they should be used and under what circumstance each…

非参数自回归中的回归式推断AI 解读

We derive a strong approximation of a local polynomial estimator LPE in nonparametric autoregression by an (LPE) in a corresponding nonparametric regression model. This generally suggests the application of regression-typical tools for statistical inference in nonparametric autoregressive models. It provides an important simplification for the boot-strap method to be used: It is enough to mimic the structure of a nonparametric regression model rather than to imitate the more…

对称统计量的经验 Edgeworth 展开AI 解读

In this paper the validity of a one-term Edgeworth expansion for Studentized symmetric statistics is proved. We propose jackknife estimates for the unknown constants appearing in the expansion and prove their consistency. As a result we obtain the second-order correctness of the empirical Edgeworth expansion for a very general class of statistics, including $U$-statistics, $L$-statistics and smooth functions of the sample mean. We illustrate the application of the bootstrap…

有限因变量模型估计的模拟得分法AI 解读

The method of simulated scores (MSS) is presented for estimating limited dependent variables models (LDV) with flexible correlation structure in the unobservables. The authors propose simulators that are continuous in the unknown parameter vectors, and hence standard optimization methods can be used to compute the MSS estimators that employ these simulators. The first continuous method relies on a recursive conditioning of the multivariate normal density through a Cholesky…

动态均衡经济：比较模型与数据的框架AI 解读

We propose a constructive, multivariate framework for assessing agreement between (generally misspecified) dynamic equilibrium models and data, which enables a complete second-order comparison of the dynamic properties of models and data. We use bootstrap algorithms to evaluate the significance of deviations between models and data, and we use goodness-of-fit criteria to produce estimators that optimize economically-relevant loss functions. We provide a detailed illustrative…

群组序贯试验置信区间的重抽样方法AI 解读

Resampling methods are introduced for the construction of confidence intervals for treatment effects associated with the primary and secondary endpoints of a clinical trial whose stopping rule is specified by a group sequential test. These methods are nonparametric and compare favourably with the exact methods that assume the responses to be normally distributed.

曲线结构平均的渐近与 Bootstrap 置信界AI 解读

For analyzing samples of curves, Kneip and Gasser proposed a “structural analysis” for estimating an average curve which gives the average amplitude and dynamics of the sample curves. An important step of their method is the estimation of the warping functions in order to eliminate the differences in dynamics between different curves. It is of interest to compute confidence bounds for the structural average curve. First, we derive the necessary asymptotic results to obtain…

Arcing 分类器：附讨论与作者答复AI 解读

Recent work has shown that combining multiple versions of unstable classifiers such as trees or neural nets results in reduced test set error. One of the more effective is bagging. Here, modified training sets are formed by resampling from the original training set, classifiers constructed using these training sets and then combined by voting. Freund and Schapire propose an algorithm the basis of which is to adaptively resample and combine (hence the acronym “arcing”) so…

结合自助法根搜索的加权似然方程AI 解读

We discuss a method of weighting likelihood equations with the aim of obtaining fully efficient and robust estimators. We discuss the case of continuous probability models using unimodal weighting functions. These weighting functions downweight observations that are inconsistent with the assumed model. At the true model, therefore, the proposed estimating equations behave like the ordinary likelihood equations. We investigate the number of solutions of the estimating…

摘要暂缺

脉冲响应函数的小样本置信区间AI 解读

Bias-corrected bootstrap confidence intervals explicitly account for the bias and skewness of the small-sample distribution of the impulse response estimator, while retaining asymptotic validity in stationary autoregressions. Monte Carlo simulations for a wide range of bivariate models show that in small samples bias-corrected bootstrap intervals tend to be more accurate than delta method intervals, standard bootstrap intervals, and Monte Carlo integration intervals. This…

基于估计分布函数的置换检验AI 解读

In this article we develop permutation tests for estimated distribution functions. The tests are formed by averaging a functional of estimated distribution functions that are calculated from independent sampling units, where the units may be a single response, a set of repeated responses, or a censored response. We study primarily two functionals—the difference in means functional and the Mann-Whitney functional, and two types of responses—repeated conditionally independent…

广义线性混合模型中的预测标准误AI 解读

The unconditional mean squared error of prediction (UMSEP) is widely used as a measure of prediction variance for inferences concerning linear combinations of fixed and random effects in the classical normal theory mixed model. But the UMSEP is inappropriate for generalized linear mixed models where the conditional variance of the random effects depends on the data. When the random effects describe variation between independent small domains and domain-specific prediction is…

回归模型检验中的自助法近似AI 解读

Let M = mθθ θ be a parametric model for an unknown regression function m. For example, M may consist of all polynomials or trigonometric polynomials with a given bound on the degree. To check the full model M (i.e., to test for H 0: m ε M), it is known that optimal tests should be based on the empirical process of the regressors marked by the residuals. In this article we show that the distribution of this process may be approximated by the wild bootstrap. The method is…

非平稳时间序列平滑的筛自助法AI 解读

We propose a sieve bootstrap procedure for time series with a deterministic trend. The sieve for constructing the bootstrap is based on nonparametric trend estimation and autoregressive approximation for some noise process. The bootstrap scheme itself does i.i.d. resampling of estimated innovations from fitted autoregressive models. We show the validity and indicate second-order correctness of such sieve bootstrap approximations for the limiting distribution of nonparametric…

摘要暂缺

贝叶斯自助法与可交换抽球方案族的扩展AI 解读

Summary A Bayesian bootstrap for a finite population with censored observations is introduced. It is shown to reduce to the finite population Bayesian bootstrap if there is no censoring and to reduce to the censored data Bayesian bootstrap for a large population. A class of general urn schemes for simulating exchangeable sequences of variables is introduced which is connected to the bootstrap method.

概率抽样中的稳健模型AI 解读

Summary In the estimation of a population mean or total from a random sample, certain methods based on linear models are known to be automatically design consistent, regardless of how well the underlying model describes the population. A sufficient condition is identified for this type of robustness to model failure; the condition, which we call ‘internal bias calibration’, relates to the combination of a model and the method used to fit it. Included among the internally…

确定身体质量指数与死亡率关系的最低点：案例研究AI 解读

Many studies have demonstrated a nonmonotonic relationship between mortality and body mass index (BMI), with excess mortality occurring at both low and high levels. Although much discussion and many different analyses have appeared, to our knowledge no attempt has been made to quantitatively establish the BMI at which minimum mortality (BMImin) occurs or to establish confidence intervals for this BMI, accounting for the asymmetry of the relationship. We model the…

复杂调查中有限总体均值的经验贝叶斯估计AI 解读

Estimation of finite population means is considered when samples are collected using a stratified sampling design. Finite populations for different strata are assumed to be realizations from different superpopulations. The true means of the observations lie on a regression surface with random intercepts for different strata. The true sampling variances are also different and random for different strata. The strata are connected through two common prior distributions, one for…