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局部多项式回归与模拟外推AI 解读

Summary The paper introduces a new local polynomial estimator and develops supporting asymptotic theory for nonparametric regression in the presence of covariate measurement error. We address the measurement error with Cook and Stefanski's simulation–extrapolation (SIMEX) algorithm. Our method improves on previous local polynomial estimators for this problem by using a bandwidth selection procedure that addresses SIMEX's particular estimation method and considers higher…

检测标记点过程中的标记与位置依赖AI 解读

Summary We introduce two characteristics for stationary and isotropic marked point proces- ses, E(h) and V(h), and describe their use in investigating mark–point interactions. These quantities are functions of the interpoint distance h and denote the conditional expectation and the conditional variance of a mark respectively, given that there is a further point of the process a distance h away. We present tests based on E and V for the hypothesis that the values of the marks…

错误发现率的强控制、保守点估计与同时保守一致性：统一方法AI 解读

Summary The false discovery rate (FDR) is a multiple hypothesis testing quantity that describes the expected proportion of false positive results among all rejected null hypotheses. Benjamini and Hochberg introduced this quantity and proved that a particular step-up p-value method controls the FDR. Storey introduced a point estimate of the FDR for fixed significance regions. The former approach conservatively controls the FDR at a fixed predetermined level, and the latter…

单一方差分量线性混合模型中的似然比检验AI 解读

Summary We consider the problem of testing null hypotheses that include restrictions on the variance component in a linear mixed model with one variance component and we derive the finite sample and asymptotic distribution of the likelihood ratio test and the restricted likelihood ratio test. The spectral representations of the likelihood ratio test and the restricted likelihood ratio test statistics are used as the basis of efficient simulation algorithms of their null…

改善正态近似的幂变换及其应用AI 解读

Summary Random variables which are positive linear combinations of positive independent random variables can have heavily right-skewed finite sample distributions even though they might be asymptotically normally distributed. We provide a simple method of determining an appropriate power transformation to improve the normal approximation in small samples. Our method contains the Wilson–Hilferty cube root transformation for χ2 random variables as a special case. We also…

有限混合模型中两组分假设的检验AI 解读

Summary We consider a finite mixture model with k components and a kernel distribution from a general one-parameter family. The problem of testing the hypothesis k=2 versusk⩾3 is studied. There has been no general statistical testing procedure for this problem. We propose a modified likelihood ratio statistic where under the null and the alternative hypotheses the estimates of the parameters are obtained from a modified likelihood function. It is shown that estimators of the…

双重自回归模型的估计与平稳性检验AI 解读

Summary The paper considers the double-autoregressive model yt = φyt−1+ɛt with ɛt =ηt√(ω+αyt−12). Consistency and asymptotic normality of the estimated parameters are proved under the condition E ln |φ +√αηt|<0, which includes the cases with |φ|=1 or |φ|>1 as well as E(εt2)=∞. It is well known that all kinds of estimators of φ in these cases are not normal when ɛt are independent and identically distributed. Our result is novel and surprising. Two tests are proposed for…

Summary We suggest two new methods, which are applicable to both deconvolution and regression with errors in explanatory variables, for nonparametric inference. The two approaches involve kernel or orthogonal series methods. They are based on defining a low order approximation to the problem at hand, and proceed by constructing relatively accurate estimators of that quantity rather than attempting to estimate the true target functions consistently. Of course, both techniques…

列联表的多项分布—泊松齐次模型AI 解读

A unified approach to maximum likelihood inference for a broad, new class of contingency table models is presented. The model class comprises multinomial-Poisson homogeneous (MPH) models, which can be characterized by an independent sampling plan and a system of homogeneous constraints, h(m) = 0, where m is the vector of expected table counts. Maximum likelihood (ML) fitting and large-sample inference for MPH models are described. The MPH models are partitioned into…

多治疗临床试验中双重自适应偏币设计的渐近性质AI 解读

A general doubly adaptive biased coin design is proposed for the allocation of subjects to K treatments in a clinical trial. This design follows the same spirit as Efron's biased coin design and applies to the cases where the desired allocation proportions are unknown, but estimated sequentially. Strong consistency, a law of the iterated logarithm and asymptotic normality of this design are obtained under some widely satisfied conditions. For two treatments, a new family of…

具有第二类偏向的分布的一致估计及竞争风险应用AI 解读

A random variable X is symmetric about 0 if X and -X have the same distribution. There is a large literature on the estimation of a distribution function (DF) under the symmetry restriction and tests for checking this symmetry assumption. Often the alternative describes some notion of skewness or one-sided bias. Various notions can be described by an ordering of the distributions of X and -X. One such important ordering is that $P(0<X<X\le x)-P(-x\le X<0)$ is increasing in $x<0$…

投影深度估计量的影响函数与最大偏差AI 解读

Location estimators induced from depth functions increasingly have been pursued and studied in the literature. Among them are those induced from projection depth functions. These projection depth based estimators have favorable properties among their competitors. In particular, they possess the best possible finite sample breakdown point robustness. However, robustness of estimators cannot be revealed by the finite sample breakdown point alone. The influence function, gross…

Stahel–Donoho 估计量与多元数据的深度加权均值AI 解读

The depth of multivariate data can be used to construct weighted means as robust estimators of location. The use of projection depth leads to the Stahel-Donoho estimator as a special case. In contrast to maximal depth estimators, the depth-weighted means are shown to be asymptotically normal under appropriate conditions met by depth functions commonly used in the current literature. We also confirm through a finite-sample study that the Stahel-Donoho estimator achieves a…

连续时间CUSUM程序的最优性AI 解读

The optimality of CUSUM under a Lorden-type criterion setting is considered. We demonstrate the optimality of the CUSUM test for Itô processes, in a sense similar to Lorden's, but with a criterion that replaces expected delays by the corresponding Kullback-Leibler divergence.

工具变量回归中结构参数子集的检验AI 解读

We develop Lagrange multiplier and likelihood ratio statistics to test hypotheses on subsets of the structural parameters in an instrumental variables regression model. The asymptotic distributions of these statistics are robust to instrument quality. A key assumption is, however, that the instruments are valid for the remaining endogenous variables. We show that the statistics lead to 95% confidence sets for the return on education in data from Card (1995) that are…

补救教育与学生成绩：一项断点回归分析AI 解读

As standards and accountability have become increasingly prominent features of the educational landscape, educators have relied more on remedial programs such as summer school and grade retention to help low-achieving students meet minimum academic standards. Yet the evidence on the effectiveness of such programs is mixed, and prior research suffers from selection bias. However, recent school reform efforts in Chicago provide an opportunity to examine the causal impact of…

参与时长不同时的学前项目评估：一种非参数方法AI 解读

Nonexperimental data are used to evaluate impacts of a Bolivian preschool program on cognitive, psychosocial, and anthropometric outcomes. Impacts are shown to be highly dependent on age and exposure duration. To minimize the effect of distributional assumptions, program impacts are estimated as nonparametric functions of age and duration. A generalized matching estimator is developed and used to control for nonrandom selectivity into the program and into exposure durations.…

何时应控制协变量？处理效应估计的面板式渐近分析AI 解读

The problem of when to control for continuous or high-dimensional discrete covariate vectors arises in both experimental and observational studies. Large-cell asymptotic arguments suggest that full control for covariates or stratification variables is always efficient, even if treatment is assigned independently of covariates or strata. Here, we approximate the behavior of different estimators using a panel-data-type asymptotic sequence with fixed cell sizes and the number…

使用匹配、工具变量与控制函数估计经济选择模型AI 解读

This paper investigates four topics. (1) It examines the different roles played by the propensity score (the probability of selection into treatment) in matching, instrumental variable, and control function methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It characterizes the sensitivity of matching to the choice of conditioning variables and demonstrates the greater robustness of control function methods to misspecification…

Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogeneity, unconfoundedness, or selection on observables. The implication of these assumptions is that systematic (for example, average or distributional) differences in outcomes…

04.1.1 基于固定效应与误差成分两阶段最小二乘差异的 Hausman 检验AI 解读

A Hausman test based on the difference between fixed effects two-stage least squares and error components two-stage least squares.

二次差分检验：去均值、去趋势方法与初始值的作用AI 解读

In this paper we investigate the impact that starting values have upon the double differencing tests of Hasza and Fuller (1979, Annals of Statistics 7, 1106–1120) and Sen and Dickey (1987, Journal of Business and Economic Statistics 5, 463–473), based on ordinary least squares (OLS) and simple symmetric least squares (SSLS) estimation, respectively. We demonstrate that, contrary to what is observed for conventional unit root tests, when based on data that have been demeaned,…

利用协变量的平稳性检验AI 解读

Two new stationarity tests are proposed. Both tests can be viewed as generalizations of existing stationarity tests and dominate these in terms of local asymptotic power. Improvements are achieved by accommodating stationary covariates. A Monte Carlo investigation of the small sample properties of the tests is conducted, and an empirical illustration from international finance is provided.This paper has benefited from the comments of Pentti Saikkonen (the co-editor), two…

近积分非高斯模型中的最优推断与稳健推断AI 解读

Elliott, Rothenberg, and Stock (1996, Econometrica 64, 813–836) derive a class of point-optimal unit root tests in a time series model with Gaussian errors. Other authors have proposed “robust” tests that are not optimal for any model but perform well when the error distribution has thick tails. I derive a class of point-optimal tests for models with non-Gaussian errors. When the true error distribution is known and has thick tails, the point-optimal tests are generally more…