日期精度：到日 1012 篇 · 到月 958 篇 · 到年 101 篇
重抽样方法中的鞍点近似
Saddlepoint approximations are shown to be easy to use and accurate in a variety of simple bootstrap and randomization applications. Examples include mean estimation, ratio estimation, two-sample comparisons, and autoregressive estimation.
相关系数自助法估计的一则札记
Smoothed bootstrap estimation of the sampling standard deviation of the variance-stabilized correlation coefficient is reconsidered. An approximation to the mean squared error of the bootstrap estimator is obtained and an empirical procedure for choosing the degree of smoothing in the bootstrap estimation is presented. Performance of the procedure is examined in a simulation study.
单个统计泛函的经验似然比置信区间
The empirical distribution function based on a sample is well known to be the maximum likelihood estimate of the distribution from which the sample was taken. In this paper the likelihood function for distributions is used to define a likelihood ratio function for distributions. It is shown that this empirical likelihood ratio function can be used to construct confidence intervals for the sample mean, for a class of M-estimates that includes quantiles, and for differentiable…
Bootstrap 的部分修正现象
The phenomenon of partial $n^{-1/2}$-term correction by the bootstrap in the estimation of sampling distributions of nonstandardized statistics is explained and studied in this note.
自回归预测误差性质的估计
Forecasting requires estimates of the error of prediction; however, such estimates for autoregressive forecasts depend nonlinearly on unknown parameters and distributions. Substitution estimators of mean squared error (MSE) possess bias that varies with the underlying model, and Gaussian-based prediction intervals fail if the data are not normally distributed. This article proposes methods that avoid these problems. A second-order Taylor expansion produces an estimator of…
向量自回归与现实
This article questions the statistical significance of variance decompositions and impulse response functions for unrestricted vector auto regressions. It suggests that previous authors have failed to provide confidence intervals for variance decompositions and impulse response functions. Two methods of computing such confidence intervals are developed: first, using a normal approximation; second, using bootstrapped resampling. An example from Sims's work is used to…
Bootstrap 与连续性校正
SUMMARY A continuity correction to the bootstrap is suggested, useful when the bootstrap is employed to approximate distributions of lattice-valued sample means. Versions of the correction are available quite generally, even in multivariate cases. Asymptotic theory reveals that the correction can reduce maximum rounding error by up to 50%. An example, where continuity correction is used in the construction of confidence intervals, illustrates the performance of the procedure…
利用秩估计回归参数
SUMMARY In this paper we consider the estimation of a regression parameter in a partially specified model where, after an unknown monotone increasing transformation, the response is normally distributed and related to an explanatory variable by a linear model. We consider a Monte Carlo resampling technique due to Doksum and various modifications of it. In addition a simple estimate based on a modification of Fisher and Yates' normal scores method and an estimate using the…
自助乘积极限过程的收敛速率
We establish rates for strong approximations of the bootstrapped product-limit process and the corresponding quantile process. These results are used to show weak convergence of bootstrapped total time on test and Lorenz curve processes to the same limiting Gaussian processes as for the unbootstrapped versions. We develop fully nonparametric confidence bands and tests for these curves and apply these results to prostate cancer. We also present almost sure results for the…
随机化估计与检验
Stochastic procedures are randomized tests, estimates and confidence sets with two properties: (i) They are functions of an original sample and one or more artificially constructed auxiliary samples. (ii) They become nearly nonrandomized when the auxiliary samples increase in size. The stochastic procedures of this paper, which arise as approximations to numerically intractable procedures, involve iterated bootstrap techniques and random sampling schemes over abstract…
配对设计中以中位数进行重新随机化推断
When a rerandomization or permutation test is applied to a matched-pairs design, the observed mean difference is typically compared with the null distribution of means that would have occurred under all possible randomizations. It is shown that rerandomizing the median instead of the mean transforms a formidable computational problem into one amenable to a hand calculator. Moreover, the robustness derived from rerandomizing the median rather than the mean is illustrated with…
自助法与基于似然的置信域
We describe a method for constructing likelihood-based confidence regions for a vector parameter, using the bootstrap and nonparametric density estimation. The technique is illustrated by application to a numerical example, and its theoretical properties are elucidated. It is argued that likelihood-based regions should not be approximated by ellipses, if we are to have any hope of capturing first-order departures from normality. Bootstrap algorithms for constructing…
通过预枢轴化降低置信集的覆盖水平误差
Approximate confidence sets for a parameter θ may be obtained by referring a function of θ and of the sample to an estimated quantile of that function's sampling distribution. We call this function the root of the confidence set. Either asymptotic theory or bootstrap methods can be used to estimate the desired quantile. When the root is not a pivot, in the sense of classical statistics, the actual level of the approximate confidence set may differ substantially from the…
未来需求的概率分布
The bootstrapping technique of Efron (1979) is used to estimate the probability distribution of future electricity demand for Hydro Quebec. The application follows the regression approach of Freedman and Peters (1984a,b) but also allows for serially correlated disturbances and uncertainty in the independent variable forecasts.
无限方差情形下均值的Bootstrap
Let $X_1, X_2, \ldots, X_n$ be independent identically distributed random variables with $EX^2_1 = \infty$ but $X_1$ belonging to the domain of attraction of a stable law. It is known that the sample mean $\bar{X}_n$ appropriately normalized converges to a stable law. It is shown here that the bootstrap version of the normalized mean has a random distribution (given the sample) whose limit is also a random distribution implying that the naive bootstrap could fail in the…
回归自适应最大似然估计的 Monte Carlo 证据
This paper reports Monte Carlo evidence on the fixed sample size properties of adaptive maximum likelihood estimates of a linear regression. The focus is on the problem of selecting the smoothing and trimming parameters used in estimating the score function. We examine the performance of adaptive maximum likelihood estimators when these parameters are preselected or, alternatively, are determined by a data-based bootstrap method.
方差估计导论
The Method of Random Groups.- Variance Estimation Based on Balanced Half-Samples.- The Jackknife Method.- The Bootstrap Method.- Taylor Series Methods.- Generalized Variance Functions.- Variance Estimation for Systematic Sampling.- Summary of Methods for Complex Surveys.- Hadamard Matrices.- Asymptotic Theory of Variance Estimators.- Transformations.- The Effect of Measurement Errors on Variance Estimation.- Computer Software for Variance Estimation.- The Effect of…
贝叶斯 bootstrap 的大样本研究
An asymptotic justification of the Bayesian bootstrap is given. Large-sample Bayesian bootstrap probability intervals for the mean, the variance and bands for the distribution, the smoothed density and smoothed rate function are also provided.
比例风险模型部分似然方法向一般变换模型的扩展
Estimates of the linear model parameters in a linear transformation model with unknown increasing transformation are obtained by maximizing a partial likelihood. A resampling scheme (likelihood sampler) is used to compute the maximum partial likelihood estimates. It is shown that for a certain "local" parameter set where the "signal to noise ratio" is small, it is asymptotically possible to estimate the linear model parameters using the partial likelihood as well as if the…
置信水平的校准
Two approaches for dealing with the problem of poor coverage probabilities of certain standard confidence intervals are proposed. The first is a recommendation that the actual coverage be estimated directly from the data and its value reported in addition to the nominal level. This is achieved through a combination of computer simulation and density estimation. The asymptotic validity of the procedure is proved for a number of common situations. A classical example is the…
改进的 Bootstrap 置信区间
We consider the problem of setting approximate confidence intervals for a single parameter θ in a multiparameter family. The standard approximate intervals based on maximum likelihood theory, , can be quite misleading. In practice, tricks based on transformations, bias corrections, and so forth, are often used to improve their accuracy. The bootstrap confidence intervals discussed in this article automatically incorporate such tricks without requiring the statistician to…
Bootstrap 置信区间与 Bootstrap 近似
The BCa bootstrap procedure (Efron 1987) for constructing parametric and nonparametric confidence intervals is considered. Like the bootstrap, this procedure can be applied to complicated problems in a wide range of situations. For models indexed by a scalar parameter θ with efficient estimator , the BCa procedure relies on the existence of a transformation g(·) such that () is approximately normally distributed with standard deviation 1 + ag(θ), although explicit knowledge…
依赖数据下的优势比推断：两种程序的关系
Liang (1985) proposed an alternative to the Mantel-Haenszel procedure for testing the significance of an estimated common odds ratio when the binomial assumption for the observed cell frequencies is relaxed. It is shown that this procedure is a form of Fisher's one-sample permutation test.