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Estimation of the truncation probability in the random truncation model

随机截断模型中截断概率的估计

Under random truncation, a pair of independent random variables $X$ and $Y$ is observable only if $X$ is larger than $Y$. The resulting model is the conditional probability distribution $H( x, y) =P[X \leq x,Y \leq y|X \geq Y]$. For the truncation probability $\alpha=P[X \geq Y]$, a proper estimate is not the sample proportion but $\alpha_n=\int G_n (s)dF_n(s)$ where $F_n$ and $G_n$ are product limit estimates of the distribution functions $F$ and$G$ of $X$ and$Y$,…

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The strong law under random truncation

随机截断下的强大数定律

The random truncation model is defined by the conditional probability distribution $H (x, y) =P[X\leq x,Y\leq y |X \geq Y] where $X$ and $Y$ are independent random variables. A problem of interest is the estimation of the distribution function $F$ of $X$ with data from the distribution $H$. Under random truncation, $F$ need not be fully identifiable from $H$ and only a part of it, say $F_0$ , is. We show that the nonparametric MLE $F_n$ of $F_0$ obeys the strong law of large numbers in the sense that for any nonnegative, measurable function $…

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Saddlepoint Approximation for Multivariate Cumulative Distribution Functions and Probability Computations in Sampling Theory and Outlier Testing

多元累积分布函数的鞍点近似及其抽样与离群检验应用

Four multivariate distributions commonly arise in sampling theory: the multinomial, multivariate hypergeometric, Dirichlet, and multivariate Pólya distributions. Second-order saddlepoint approximations are given for approximating these multivariate cumulative distribution functions (cdf's) in their most general settings. Probabilities of rectangular regions associated with these cdf's are also approximated directly using second-order saddlepoint methods. All the…

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Balanced Repeated Replication for Stratified Multistage Survey Data under Imputation

插补下分层多阶段调查数据的平衡重复复制

Balanced repeated replication (BRR) is a popular method for variance estimation in surveys. The standard BRR method works by first creating a set of “balanced” pseudoreplicated datasets from the original dataset. For a survey estimator θ, the BRR variance estimator is the average of squared deviations θ(r) – θ, where θ(r) is the same as θ but based on the data in the rth pseudoreplicated dataset only. But when there are a large number of imputed missing values…

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A Multivariate MultiSample Quantile Test for Ordered Alternatives

针对有序备择的多元多样本分位数检验

We propose and study a multivariate c-sample rank test for order-restricted alternatives when the underlying distributions have a contaminated component. An example concerning lens opacity in adults is presented. The asymptotic distributions are obtained under local mixture alternatives, and Pitman efficiencies are calculated. An empirical power study is also included.

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Balanced Repeated Replication for Stratified Multistage Survey Data under Imputation

插补条件下分层多阶段调查数据的平衡重复复制法

Balanced repeated replication (BRR) is a popular method for variance estimation in surveys. The standard BRR method works by first creating a set of “balanced” pseudoreplicated datasets from the original dataset. For a survey estimator θ, the BRR variance estimator is the average of squared deviations θ(r) – θ, where θ(r) is the same as θ but based on the data in the rth pseudoreplicated dataset only. But when there are a large number of imputed missing values…

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A Multivariate MultiSample Quantile Test for Ordered Alternatives

针对有序备择的多元多样本分位数检验

We propose and study a multivariate c-sample rank test for order-restricted alternatives when the underlying distributions have a contaminated component. An example concerning lens opacity in adults is presented. The asymptotic distributions are obtained under local mixture alternatives, and Pitman efficiencies are calculated. An empirical power study is also included.

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Saddlepoint Approximation for Multivariate Cumulative Distribution Functions and Probability Computations in Sampling Theory and Outlier Testing

多元累积分布函数的鞍点近似及其在抽样理论与异常值检验中的概率计算

Four multivariate distributions commonly arise in sampling theory: the multinomial, multivariate hypergeometric, Dirichlet, and multivariate Pólya distributions. Second-order saddlepoint approximations are given for approximating these multivariate cumulative distribution functions (cdf's) in their most general settings. Probabilities of rectangular regions associated with these cdf's are also approximated directly using second-order saddlepoint methods. All the…

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An Alternative Estimator for the Censored Quantile Regression Model

线性删失分位数回归模型的一种替代估计量

This paper introduces an alternative estimator for the linear censored quantile regression model. The estimator also applies to cases where the censoring point is unknown. Since the objective function is globally convex and the estimator is a solution to a linear programming problem, a global minimizer is obtained in a finite number of simplex iterations. The estimator has a square root of n-convergence rate and is asymptotically normal. A Monte Carlo study performed shows…

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Limiting distributions for $L\sb 1$ regression estimators under general conditions

一般条件下L₁回归估计量的极限分布

It is well known that $L_1$-estimators of regression parameters are asymptotically normal if the distribution function has a positive derivative at 0. In this paper, we derive the asymptotic distributions under more general conditions on the behavior of the distribution function near 0.

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Necessary and sufficient conditions for weak consistency of the median of independent but not identically distributed random variables

独立非同分布随机变量样本中位数弱一致性的充要条件

Necessary and sufficient conditions for the weak consistency of the sample median of independent, but not identically distributed random variables are given and discussed.

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Asymptotic comparison of step-down and step-up multiple test procedures based on exchangeable test statistics

可交换检验统计量下逐步下降与逐步上升多重检验的渐近比较

In this paper interest is focused on some theoretical investigations concerning the comparison of two popular multiple test procedures, so-called step-down and step-up procedures, in terms of their defining critical values. Such procedures can be applied, for example, to multiple comparisons with a control. In the definition of the critical values for these procedures order statistics play a central role. For $k \epsilon N_0$ fixed we consider the joint cumulative…

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CENTRAL LIMIT AND FUNCTIONAL CENTRAL LIMIT THEOREMS FOR HILBERT-VALUED DEPENDENT HETEROGENEOUS ARRAYS WITH APPLICATIONS

Hilbert 空间值依赖异质数组的中心极限定理与函数中心极限定理及应用

We obtain new central limit theorems (CLT's) and functional central limit theorems (FCLT's) for Hilbert-valued arrays near epoch dependent on mixing processes, and also new FCLT's for general Hilbert-valued adapted dependent heterogeneous arrays. These theorems are useful in delivering asymptotic distributions for parametric and nonparametric estimators and their functionals in time series econometrics. We give three significant applications for near epoch dependent…

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Median Unbiased Estimation of Coefficient Variance in a Time-Varying Parameter Model

时变参数模型中系数方差的中位数无偏估计

This article considers inference about the variance of coefficients in time-varying parameter models with stationary regressors. The Gaussian maximum likelihood estimator (MLE) has a large point mass at 0. We thus develop asymptotically median unbiased estimators and asymptotically valid confidence intervals by inverting quantile functions of regression-based parameter stability test statistics, computed under the constant-parameter null. These estimators have good…

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Permutation Tests Using Estimated Distribution Functions

基于估计分布函数的置换检验

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…

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Confidence Intervals with More Power to Determine the Sign: Two Ends Constrain the Means

更有能力判定均值符号的置信区间:两端约束均值

We present two new families of two-sided nonequivariant confidence intervals for the mean θ of a continuous, unimodal, symmetric random variable. Compared with the conventional symmetric equivariant confidence interval, they are shorter when the observation is small, and restrict the sign of θ for smaller observations. One of the families, a modification of Pratt's construction of intervals with minimal expected length when θ = 0, is longer than the conventional symmetric…

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Local Linear Quantile Regression

局部线性分位数回归

In this article we study nonparametric regression quantile estimation by kernel weighted local linear fitting. Two such estimators are considered. One is based on localizing the characterization of a regression quantile as the minimizer of E{pp (Y — a)|X = x}, where ρp is the appropriate “check” function. The other follows by inverting a local linear conditional distribution estimator and involves two smoothing parameters, rather than one. Our aim is to present fully…

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The Statistical Theory of Shape

形状的统计理论

1 Introduction.- 1.1 Background of Shape Theory.- 1.2 Principles of Allometry.- 1.3 Defining and Comparing Shapes.- 1.4 A Few More Examples.- 1.4.1 A Simple Example in One Dimension.- 1.4.2 Dinosaur Trackways From Mt. Tom, Massachusetts.- 1.4.3 Bronze Age Post Mold Configurations in England.- 1.5 The Problem of Homology.- 1.6 Notes.- 1.7 Problems.- 2 Background Concepts and Definitions.- 2.1 Transformations on Euclidean Space.- 2.1.1 Properties of Sets.- 2.1.2 Affine…

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Confidence Intervals with More Power to Determine the Sign: Two Ends Constrain the Means

更有能力判定均值符号的置信区间:两端约束均值

We present two new families of two-sided nonequivariant confidence intervals for the mean θ of a continuous, unimodal, symmetric random variable. Compared with the conventional symmetric equivariant confidence interval, they are shorter when the observation is small, and restrict the sign of θ for smaller observations. One of the families, a modification of Pratt's construction of intervals with minimal expected length when θ = 0, is longer than the conventional symmetric…

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Optimal rates of convergence for estimates of the extreme value index

极值指数估计的最优收敛速度

Hall and Welsh established the best attainable rate of convergence for estimates of a positive extreme value index $\gamma$ under a certain second order condition implying that the distribution function of the maximum of n random variables converges at an algebraic rate to the pertaining extreme value distribution. As a first generalization, we obtain a surprisingly sharp bound on the estimation error if $\gamma$ is still assumed to be positive, but the rate of convergence…

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A CONSISTENT NONPARAMETRIC TEST OF PARAMETRIC REGRESSION MODELS UNDER CONDITIONAL QUANTILE RESTRICTIONS

条件分位数约束下参数回归模型的一致非参数检验

This paper proposes a nonparametric, kernel-based test of parametric quantile regression models. The test statistic has a limiting standard normal distribution if the parametric quantile model is correctly specified and diverges to infinity for any misspecification of the parametric model. Thus the test is consistent against any fixed alternative. The test also has asymptotic power 1 against local alternatives converging to the null at proper rates. A simulation study is…

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Nonparametric Validation of Similar Distributions and Assessment of Goodness of Fit

相似分布的非参数验证与拟合优度评估

Summary In this paper the problem of assessing the similarity of two cumulative distribution functions F and G is considered. An asymptotic test based on an α-trimmed version of Mallows distance Γα(F, G) between F and G is suggested, thus demonstrating the similarity of F and G within a preassigned Γα(F, G) neighbourhood at a controlled type I error rate. The test proposed is applied to the validation of goodness of fit and for the nonparametric assessment of bioequivalence.…

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