论文检索

非参数曲线估计中的Edgeworth展开与Bootstrap置信带AI 解读

SUMMARY The notion of pivoting and techniques of Edgeworth expansion have become basic tools for using and understanding bootstrap methods in finite parameter problems. This paper shows that these ideas have important contributions to make to infinite parameter problems, e.g. in the construction of simultaneous confidence bands for nonparametric density estimators. We propose a bootstrap method for confidence band construction based on a pivotal function estimator and…

Jackknife 分布函数估计量的一项改进AI 解读

In a recent paper, C. F. J. Wu showed that the jackknife estimator of a distribution function has optimal convergence rate $O(n^{-1/2})$, where $n$ denotes the sample size. This rate is achieved by retaining $O(n)$ data values from the original sample during the jackknife algorithm. Wu's result is particularly important since it permits a direct comparison of jackknife and bootstrap methods for distribution estimation. In the present paper we show that a very simple,…

更新理论中的非参数估计之一：经验更新函数AI 解读

We introduce a nonparametric estimator for the renewal function and discuss its properties, including consistency, asymptotic normality and asymptotic validity of bootstrap confidence regions. The underlying theme is that stochastic models can be regarded as functionals or nonlinear operators. This view leads to nonparametric estimators in a natural way and statistical properties of the estimators can be related to the local behaviour of the functionals.

有界随机变量线性组合的改进Eaton界及统计应用AI 解读

The problem of evaluating tail probabilities for linear combinations of independent, possibly nonidentically distributed, bounded random variables arises in various statistical contexts, mainly connected with nonparametric inference. A remarkable inequality on such tail probabilities has been established by Eaton. The significance of Eaton's inequality is substantiated by a recent result of Pinelis showing that the minimum B EP of Eaton's bound B E and a traditional…

漏计估计中未确定登记状态插补的层级逻辑回归模型AI 解读

In the process of collecting Post-Enumeration Survey (PES) data to evaluate census coverage, it is inevitable that there will be some individuals whose enumeration status (outcome in the census-PES match) remains unresolved even after extensive field follow-up operations. Earlier work developed a logistic regression framework for imputing the probability that unresolved individuals were enumerated in the census, so that the probability of having been enumerated is allowed to…

自适应位置估计中平滑参数的交叉验证选择AI 解读

Abstract This article proposes a new data-driven method for selecting the smoothing parameter involved in constructing kernel-based adaptive location estimators. The method consists of minimizing a cross-validatory criterion with respect to the bandwidth occurring in the kernel-type estimators of the efficient score function. It is shown that the location estimator with a data-driven bandwidth selector is indeed an adaptive estimator. A simulation study reveals that the…

非对称分布均值检验的计算密集方法AI 解读

For one-sided tests about the mean of a skewed distribution, the t test is asymptotically robust for validity; however, it can be quite inaccurate and inefficient with small sample sizes. Results presented here confirm that a procedure due to Johnson should be preferred to the t test when the parent distribution is asymmetrical, because it reduces the probability of type I error in cases where the t test has an inflated type I error rate and it is more powerful in other…

自适应位置估计中平滑参数的交叉验证选择AI 解读

This article proposes a new data-driven method for selecting the smoothing parameter involved in constructing kernel-based adaptive location estimators. The method consists of minimizing a cross-validatory criterion with respect to the bandwidth occurring in the kernel-type estimators of the efficient score function. It is shown that the location estimator with a data-driven bandwidth selector is indeed an adaptive estimator. A simulation study reveals that the method is…

各向异性粒子问题的形状分析AI 解读

SUMMARY The problem of inferring the shape distribution of anisotropically oriented spheroidal particles from their elliptical traces in planar samples is addressed by generalizing a size-shape independence condition suggested by Wicksell in his original discussion of the corpuscle problem. Shape statistics are introduced through which the eccentricities of the sampled ellipses may be related to some suitably defined moments of the underlying particle shape distribution,…

非线性动态结构AI 解读

Methods for nonlinear impulse response analysis are introduced. The methods are based on conditional moment profiles defined for a stationary time series. Comparing conditional moment profiles to baseline profiles is the nonlinear analog of conventional impulse-response analysis. The bootstrap may be used for statistical inference. Profile bundles may be examined for evidence of damping or persistence. Application to bivariate NYSE price and volume series from 1928 to 1987…

摘要暂缺

基于投影的偏差稳健回归估计AI 解读

A new class of bias-robust estimates of multiple regression is introduced. If $y$ and $x$ are two real random variables, let $T(y, x)$ be a univariate robust estimate of regression of $y$ on $x$ through the origin. The regression estimate $\mathbf{T}(y, \mathbf{x})$ of a random variable $y$ on a random vector $\mathbf{x} = (x_1,\cdots, x_p)'$ is defined as the vector $\mathbf{t} \in \mathfrak{R}^p$ which minimizes $\sup_{\|\mathbf{\lambda}\| = 1} \mid T(y - \mathbf{t'x, \lambda' x}) \mid s(\mathbf{\lambda'x})$…

等变性与复合决策问题AI 解读

This paper obtains some extensions of Gilliland and Hannan's results on equivariance and the compound decision problem. Consider a compound decision problem with restricted component risk and component distributions in a norm compact set of mutually absolutely continuous probability measures. Then the method of proof of a theorem of Gilliland and Hannan translates the results of Mashayekhi on symmetrization of product measures into uniform convergence to zero of the excess…

营养吸收速率方程的非参数估计AI 解读

Knowledge of the rate of a biological process is important for characterizing the system and is necessary for gaining a deeper understanding of the process. Consider measurements, Y, made over time on a system following the model Y = f(t) + e, where f is a smooth, unknown function and e is measurement error. Although most statistical methodology has focused on estimating f(t) or f′(t), in some applications what is of real biological interest is the relationship between f and…

通过交叉验证选择线性模型AI 解读

We consider the problem of selecting a model having the best predictive ability among a class of linear models. The popular leave-one-out cross-validation method, which is asymptotically equivalent to many other model selection methods such as the Akaike information criterion (AIC), the C p , and the bootstrap, is asymptotically inconsistent in the sense that the probability of selecting the model with the best predictive ability does not converge to 1 as the total number of…

模拟极端次序统计量的半参数自助法AI 解读

We propose a technique for simulating the joint distribution of the j largest order statistics of a very large sample. We assume that the parent population is in the domain of attraction of the Type 1 (Gumbel) extreme value distribution. The bootstrap variates are generated by resampling the normalized spacings of the k largest observed values in the original data where k is larger than j. We compare the bootstrap distribution to the fitted extremal distribution of Weissman.…

养分吸收速率方程的非参数估计AI 解读

Knowledge of the rate of a biological process is important for characterizing the system and is necessary for gaining a deeper understanding of the process. Consider measurements, Y, made over time on a system following the model Y = f(t) + e, where f is a smooth, unknown function and e is measurement error. Although most statistical methodology has focused on estimating f(t) or f′(t), in some applications what is of real biological interest is the relationship between f and…

模拟极端次序统计量的半参数自助法AI 解读

We propose a technique for simulating the joint distribution of the j largest order statistics of a very large sample. We assume that the parent population is in the domain of attraction of the Type 1 (Gumbel) extreme value distribution. The bootstrap variates are generated by resampling the normalized spacings of the k largest observed values in the original data where k is larger than j. We compare the bootstrap distribution to the fitted extremal distribution of Weissman.…

摘要暂缺

预测区间的计算AI 解读

Several general approaches to calculating interval forecasts are described and compared. They include the use of theoretical formulae based on a fitted probability model, various "approximate" formulae (which should be avoided), and empirically-based, simulation, and resampling procedures. Some gener al comments are made as to why prediction intervals tend to be too narr ow in practice to encompass the required proportion of future observations. An example demonstrates the…

用于自助法的平衡重要性重抽样AI 解读

We show that the method of importance resampling, introduced by Vernon Johns and Anthony Davison, may be enhanced by balancing the resamples. It is demonstrated that "balanced importance resampling" improves on both "balanced uniform resampling" and "random importance resampling", from the viewpoint of statistical efficiency. Moreover, the range of applications for which efficient resampling methods may be applied is extended to include statistics which are smooth functions…

删失数据的贝叶斯自助法AI 解读

A Bayesian bootstrap for a censored data model is introduced. Its small sample distributional properties are discussed and found to be similar to Efron's bootstrap for censored data. In the absence of censoring, the Bayesian bootstrap for censored data reduces to Rubin's Bayesian bootstrap for complete data. A first-order large-sample theory is developed. This theory shows that both censored data bootstraps are consistent bootstraps for approximating the sampling…

高维线性模型的自助法与野生自助法AI 解读

In this paper two bootstrap procedures are considered for the estimation of the distribution of linear contrasts and of F-test statistics in high dimensional linear models. An asymptotic approach will be chosen where the dimension p of the model may increase for sample size $n\rightarrow\infty$. The range of validity will be compared for the normal approximation and for the bootstrap procedures. Furthermore, it will be argued that the rates of convergence are different for…

物种数量估计：综述AI 解读

How many kinds are there? Suppose that a population is partitioned into C classes. In many situations interest focuses not on estimation of the relative sizes of the classes, but on estimation of C itself. For example, biologists and ecologists may be interested in estimating the number of species in a population of plants or animals, numismatists may be concemed with estimating the number of dies used to produce an ancient coin issue, and linguists may be interested in…