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Local Adaptive Importance Sampling for Multivariate Densities with Strong Nonlinear Relationships

适用于强非线性关系多元密度的局部自适应重要性抽样

We consider adaptive importance sampling techniques that use kernel density estimates at each iteration as importance sampling functions. These can provide more nearly constant importance weights and more precise estimates of quantities of interest than the sampling importance resampling algorithm when the initial importance sampling function is diffuse relative to the target. We propose a new method that adapts to the varying local structure of the target. When the target…

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A Note on Bootstrapping Generalized Method of Moments Estimators

关于 GMM 估计量 Bootstrap 的一则说明

Recently, Arcones and Giné (1992, pp. 13–47, in R. LePage & L. Billard [eds.], Exploring the Limits of Bootstrap, New York: Wiley) established that the bootstrap distribution of the M -estimator converges weakly to the limit distribution of the estimator in probability. In contrast, Brown and Newey (1992, Bootstrapping for GMM, Seminar note) discovered that the bootstrap distribution of the GMM overidentification test statistic does not converge weakly to the x 2…

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Direct use of regression quantiles to construct confidence sets in linear models

直接利用回归分位数构造线性模型置信集

Direct use of the empirical quantile function provides a standard distribution-free approach to constructing confidence intervals and confidence bands for population quantiles. We apply this method to construct confidence intervals and confidence bands for regression quantiles and to construct prediction intervals based on sample regression quantiles. Comparison of the direct method with the studentization and the bootstrap methods are discussed. Simulation results show that…

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Sequential Iterated Bootstrap Confidence Intervals

SUMMARY A version of the sequential probability ratio test for testing simultaneously a set of nested hypotheses is developed. This procedure is then applied to define a sequential procedure of sampling at the inner level of the two nested levels of resampling required by Monte Carlo construction of an iterated bootstrap percentile method confidence interval. The sequential resampling scheme reduces very significantly the computational demands of construction of the iterated…

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Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures

断点内生选择下的结构稳定性检验:解析与自助法的尺寸比较

We compare the performance of two alternative approximations to the finite-sample distributions of test statistics for structural change, one based on asymptotics and one based on the bootstrap. We focus on tests acknowledging that the breakpoint is selected endogenously — in particular, the ‘supremum’ tests of Andrews (1993). We explore a variety of issues of interest in applied work, focusing particularly on smaller samples and persistent dynamics. The bootstrap…

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On bandwidth choice in nonparametric regression with both short- and long-range dependent errors

短程与长程相关误差下非参数回归的带宽选择

We analyse methods based on the block bootstrap and leave-out cross-validation, for choosing the bandwidth in nonparametric regression when errors have an almost arbitrarily long range of dependence. A novel analytical device for modelling the dependence structure of errors is introduced. This allows a concise theoretical description of the way in which the range of dependence affects optimal bandwidth choice. It is shown that, provided block length or leave-out number,…

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On the minimisation of $L\sp p$ error in mode estimation

众数估计中 L^p 误差的最小化

We show that, for $L^p$ convergence of the mode of a nonparametric density estimator to the mode of an unknown probability density, finiteness of the pth moment of the underlying distribution is both necessary and sufficient. The basic requirement of existence of finite variance has been overlooked by statisticians, who have earlier considered mean square convergence of nonparametric mode estimators; they have focussed on mean squared error of the asymptotic distribution,…

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Bootstrap Inference for a First-Order Autoregression with Positive Innovations

正值创新一阶自回归模型的 Bootstrap 推断

In this article we consider statistical inference for the autoregressive parameter of a first-order autoregressive sequence with positive innovations via an extreme value estimator ϕ. We show that a bootstrap procedure correctly estimates the sampling distribution of an asymptotically pivotal quantity (whose distribution depends only on the exponent of regular variation of the innovation distribution) based on ϕ, provided that the ratio of the bootstrap sample size m and the…

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Stochastic Modeling of Early Hematopoiesis

早期造血过程的随机建模

Hematopoiesis is the body's way of making the cellular constituents of blood. Oxygen transport, response to infections, and control of bleeding are among the functions of different mature blood cells. These specific functions are acquired as cells mature in the bone marrow. Stem cells are the “master cells” at the top of this pedigree, having within them the capacity to reconstitute the entire system. Although the latter stages of hematopoiesis are fairly well understood,…

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Bootstrap Inference for a First-Order Autoregression with Positive Innovations

正创新一阶自回归模型的自助法推断

In this article we consider statistical inference for the autoregressive parameter of a first-order autoregressive sequence with positive innovations via an extreme value estimator ϕ. We show that a bootstrap procedure correctly estimates the sampling distribution of an asymptotically pivotal quantity (whose distribution depends only on the exponent of regular variation of the innovation distribution) based on ϕ, provided that the ratio of the bootstrap sample size m and the…

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Stochastic Modeling of Early Hematopoiesis

早期造血过程的随机建模

Hematopoiesis is the body's way of making the cellular constituents of blood. Oxygen transport, response to infections, and control of bleeding are among the functions of different mature blood cells. These specific functions are acquired as cells mature in the bone marrow. Stem cells are the “master cells” at the top of this pedigree, having within them the capacity to reconstitute the entire system. Although the latter stages of hematopoiesis are fairly well understood,…

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Nonparametric Tests for Nonstandard Change-Point Problems

We consider independent random elements $X_1, \ldots, X_n, n \in \mathbb{N}$, with values in a measurable space $(\mathscr{X}, \mathscr{B})$ so that $X_1, \ldots, X_{\lbrack n\theta\rbrack}$ have a common distribution $\nu_1$ and the remaining $X_{\lbrack n\theta\rbrack + 1}, \ldots, X_n$ have a common distribution $\nu_2 \neq \nu_1$, for some $\theta \in (0, 1)$. The change point $\theta$ as well as the distributions are unknown. A family of tests is introduced for the…

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The Asymptotic Accuracy of the Bootstrap of $U$-Quantiles

U 分位数自助法的渐近精度

The order of the Kolmogorov-Smirnov distance for the bootstrap of $U$-quantiles is considered. We observe that the order of the bootstrap of $U$-quantiles depends on the order of the local variance of the first term of the Hoeffding decomposition at the $U$-quantile. This order can be smaller than the order of the bootstrap of quantiles: $U$-quantiles can be smoother than quantiles.

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On the Asymptotic Behaviour of the Moving Block Bootstrap for Normalized Sums of Heavy-Tail Random Variables

重尾随机变量归一化和的移动区块自助法渐近行为

This paper studies the performance of the moving block bootstrap procedure for normalized sums of dependent random variables. Suppose that $X_1, X_2,\ldots$ are stationary $\rho$-mixing random variables with $\sum \rho (2^i) < \infty$. Let $T_n = (X_1 + \cdots + X_n - b_n)/a_n$, for some suitable constants $a_n$ and $b_n$, and let $T^\ast_{m,n}$ denote the moving block bootstrap version of $T_n$ based on a bootstrap sample of size $m$. Under certain regularity conditions, it…

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Asymptotic Iterated Bootstrap Confidence Intervals

迭代 Bootstrap 置信区间的渐近近似

An iterated bootstrap confidence interval requires an additive correction to be made to the nominal coverage level of an uncorrected interval. Such correction is usually performed using a computationally intensive Monte Carlo simulation involving two nested levels of bootstrap sampling. Asymptotic expansions of the required correction and the iterated interval endpoints are used to provide two new computationally efficient methods for constructing an approximation to the…

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Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study

分位数回归模型渐近协方差矩阵估计的蒙特卡洛研究

This Monte Carlo study examines several estimation procedures of the asymptotic covariance matrix in the quantile and censored quantile regression models: design matrix bootstrap, error bootstrapping, order statistic, sigma bootstrap, homoskedastic kernel, and heteroskedastic kernel. The Monte Carlo samples are drawn from two alternative data sets: (a) the unaltered Current Population Survey (CPS) for 1987 and (b) this CPS data with independence between error term and…

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Exact Multivariate Bayesian Bootstrap Distributions of Moments

矩的精确多元贝叶斯Bootstrap分布

The common unknown probability law $P$ of a random sample $Y_1,\ldots, Y_n$ is assigned a Dirichlet process prior with index $\alpha$. It is shown that the posterior joint density of several moments of $P$ converges, as $\alpha(\mathbb{R})\rightarrow 0$, to a multivariate B-spline, which is, therefore, the Bayesian bootstrap joint density of the moments. The result provides the basis for possible default nonparametric Bayesian inference on unknown moments.

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Martingale Expansions and Second Order Inference

鞅展开与二阶推断

The paper develops a one-step triangular array Edgeworth expansion for multivariate martingales that are, essentially, asymptotically ergodic. Both discrete and continuous time are covered. The expansion is in a test function topology. We investigate when the expansion has the usual Edgeworth form, looking in particular at likelihood inference, including Cox regression, and at inference for stationary time series. The triangular array nature of the results make them useful…

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Efficiency and Power of Tests for Multiple Binary Outcomes

多个二元结局检验的效率与功效

Global tests provide a useful tool for comparing two or more groups with respect to multiple correlated outcomes. We adapt and compare the performance of tests that have been suggested for use with multiple continuous outcomes to the case of multiple binary outcomes. Comparisons and guidelines are based on asymptotic relative efficiencies (ARE's) and simulations. These results are illustrated using an application from teratology. We extend the work of Lefkopoulou and Ryan to…

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Statistical Analysis of Circular Data.

圆形数据的统计分析

Preface 1. The purpose of the book 2. Survey of contents 3. How to use the book 4. Notation, terminology and conventions 5. Acknowledgements Part I. Introduction: Part II. Descriptive Methods: 2.1. Introduction 2.2. Data display 2.3. Simple summary quantities 2.4. Modifications for axial data Part III. Models: 3.1. Introduction 3.2. Notation trigonometric moments 3.3. Probability distributions on the circle Part IV. Analysis of a Single Sample of Data: 4.1. Introduction 4.2.…

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Efficiency and Power of Tests for Multiple Binary Outcomes

多个二元结局检验的效率与功效

Global tests provide a useful tool for comparing two or more groups with respect to multiple correlated outcomes. We adapt and compare the performance of tests that have been suggested for use with multiple continuous outcomes to the case of multiple binary outcomes. Comparisons and guidelines are based on asymptotic relative efficiencies (ARE's) and simulations. These results are illustrated using an application from teratology. We extend the work of Lefkopoulou and Ryan to…

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Additivity Tests for Nonlinear Autoregression

非线性自回归的可加性检验

Additivity is commonly used in the statistical literature to simplify data analysis, especially in analysis of variance and in multivariate smoothing. In this paper, we propose three procedures for testing additivity in nonlinear time series analysis. The first procedure combines some smoothing techniques with analysis of variance, the second is a Lagrange multiplier test using nonparametric estimation, and the third is a permutation test which uses smoothing techniques to…

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