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Testing for structural change in regression with long memory processes

长记忆回归过程中的结构变化检验

The paper considers tests for structural change in time series regression models where both regressors and residuals may exhibit long range dependence. The limiting distribution of the test statistic depends on unknown parameters and is approximated by a bootstrap procedure. The asymptotic validity of bootstrap is shown and performance of the testing procedure is examined in a simple Monte Carlo experiment.

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A parametric bootstrap test for cycles

周期性的参数自助检验

The paper proposes a simple test for the hypothesis of strong cycles and as a by-product a test for weak dependence for linear processes. We show that the limit distribution of the test is the maximum of a (semi)Gaussian process G (τ), τ ∈ [0; 1]. Because the covariance structure of G (τ) is a complicated function of τ and model dependent, to obtain the critical values (if possible) of maxτ∈[0;1] G (τ) may be difficult. For this reason we propose a bootstrap scheme in the…

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Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a Studentized statistic

学生化统计量自助分位数的自助后刀切方差估计一致性

Efron [J. Roy. Statist. Soc. Ser. B 54 (1992) 83–111] proposed a computationally efficient method, called the jackknife-after-bootstrap, for estimating the variance of a bootstrap estimator for independent data. For dependent data, a version of the jackknife-after-bootstrap method has been recently proposed by Lahiri [Econometric Theory 18 (2002) 79–98]. In this paper it is shown that the jackknife-after-bootstrap estimators of the variance of a bootstrap quantile are…

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Order selection for same-realization predictions in autoregressive processes

自回归过程中同一实现预测的阶数选择

Assume that observations are generated from an infinite-order autoregressive [AR(∞)] process. Shibata [Ann. Statist. 8 (1980) 147–164] considered the problem of choosing a finite-order AR model, allowing the order to become infinite as the number of observations does in order to obtain a better approximation. He showed that, for the purpose of predicting the future of an independent replicate, Akaike’s information criterion (AIC) and its variants are asymptotically…

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High moment partial sum processes of residuals in GARCH models and their applications

GARCH 模型残差的高阶矩部分和过程及其应用

In this paper we construct high moment partial sum processes based on residuals of a GARCH model when the mean is known to be 0. We consider partial sums of kth powers of residuals, CUSUM processes and self-normalized partial sum processes. The kth power partial sum process converges to a Brownian process plus a correction term, where the correction term depends on the kth moment μk of the innovation sequence. If μk=0, then the correction term is 0 and, thus, the kth power…

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Cross-validation in nonparametric regression with outliers

含离群值非参数回归中的交叉验证

A popular data-driven method for choosing the bandwidth in standard kernel regression is cross-validation. Even when there are outliers in the data, robust kernel regression can be used to estimate the unknown regression curve [Robust and Nonlinear Time Series Analysis. Lecture Notes in Statist. (1984) 26 163–184]. However, under these circumstances standard cross-validation is no longer a satisfactory bandwidth selector because it is unduly influenced by extreme prediction…

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Penalized log-likelihood estimation for partly linear transformation models with current status data

现时状态数据下部分线性变换模型的惩罚对数似然估计

We consider partly linear transformation models applied to current status data. The unknown quantities are the transformation function, a linear regression parameter and a nonparametric regression effect. It is shown that the penalized MLE for the regression parameter is asymptotically normal and efficient and converges at the parametric rate, although the penalized MLE for the transformation function and nonparametric regression effect are only n1/3 consistent. Inference…

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Asymptotic normality of the Lk-error of the Grenander estimator

Grenander 估计量的 Lk 误差渐近正态性

We investigate the limit behavior of the \(L_k\)-distance between a decreasing density \(f\) and its nonparametric maximum likelihood estimator \(\hat{f}_n\) for \(k \geq 1\). Due to the inconsistency of \(\hat{f}_n\) at zero, the case \(k = 2.5\) turns out to be a kind of transition point. We extend asymptotic normality of the \(L_1\)-distance to the \(L_k\)-distance for \(1 \leq k < 2.5\), and obtain the analogous limiting result for a modification of the \(L_k\)-distance…

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Wavelet thresholding for nonnecessarily Gaussian noise: Functionality

非必为高斯噪声下的小波阈值法:功能表现

For signals belonging to balls in smoothness classes and noise with enough moments, the asymptotic behavior of the minimax quadratic risk among soft-threshold estimates is investigated. In turn, these results, combined with a median filtering method, lead to asymptotics for denoising heavy tails via wavelet thresholding. Some further comparisons of wavelet thresholding and of kernel estimators are also briefly discussed.

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Asymptotic results for maximum likelihood estimators in joint analysis of repeated measurements and survival time

重复测量与生存时间联合分析中极大似然估计的渐近结果

Maximum likelihood estimation has been extensively used in the joint analysis of repeated measurements and survival time. However, there is a lack of theoretical justification of the asymptotic properties for the maximum likelihood estimators. This paper intends to fill this gap. Specifically, we prove the consistency of the maximum likelihood estimators and derive their asymptotic distributions. The maximum likelihood estimators are shown to be semiparametrically efficient.

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Asymptotic behavior of the unconditional NPMLE of the length-biased survivor function from right censored prevalent cohort data

右删失现患队列中长度偏倚生存函数无条件非参数最大似然估计的渐近行为

Right censored survival data collected on a cohort of prevalent cases with constant incidence are length-biased, and may be used to estimate the length-biased (i.e., prevalent-case) survival function. When the incidence rate is constant, so-called stationarity of the incidence, it is more efficient to use this structure for unconditional statistical inference than to carry out an analysis by conditioning on the observed truncation times. It is well known that, due to the…

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Nonparametric estimation of mixing densities for discrete distributions

离散分布混合密度的非参数估计

By a mixture density is meant a density of the form πμ(⋅)=∫πθ(⋅)×μ(dθ), where (πθ)θ∈Θ is a family of probability densities and μ is a probability measure on Θ. We consider the problem of identifying the unknown part of this model, the mixing distribution μ, from a finite sample of independent observations from πμ. Assuming that the mixing distribution has a density function, we wish to estimate this density within appropriate function classes. A general approach is proposed…

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Estimation of sums of random variables: Examples and information bounds

随机变量函数之和的估计:实例与信息界

This paper concerns the estimation of sums of functions of observable and unobservable variables. Lower bounds for the asymptotic variance and a convolution theorem are derived in general finite- and infinite-dimensional models. An explicit relationship is established between efficient influence functions for the estimation of sums of variables and the estimation of their means. Certain “plug-in” estimators are proved to be asymptotically efficient in finite-dimensional…

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Recursive Monte Carlo filters: Algorithms and theoretical analysis

递归蒙特卡洛滤波:算法与理论分析

Recursive Monte Carlo filters, also called particle filters, are a powerful tool to perform computations in general state space models. We discuss and compare the accept–reject version with the more common sampling importance resampling version of the algorithm. In particular, we show how auxiliary variable methods and stratification can be used in the accept–reject version, and we compare different resampling techniques. In a second part, we show laws of large numbers and a…

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Estimation and Testing of Forecast Rationality under Flexible Loss

灵活损失函数下预测理性的估计与检验

In situations where a sequence of forecasts is observed, a common strategy is to examine "rationality" conditional on a given loss function. We examine this from a different perspective—supposing that we have a family of loss functions indexed by unknown shape parameters, then given the forecasts can we back out the loss function parameters consistent with the forecasts being rational even when we do not observe the underlying forecasting model? We establish identification…

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Panel Stationarity Tests for Purchasing Power Parity With Cross-Sectional Dependence

允许横截面依赖的购买力平价面板平稳性检验

We investigate the purchasing power parity (PPP) hypothesis for a group of 17 countries using a new panel-based test of stationarity that allows for arbitrary cross-sectional dependence. We treat the short-run time series dynamics nonparametrically and thus avoid the need to fit separate, and potentially misspecified, models for the individual series. The statistic is simple to compute and uses standard normal critical values, even in the presence of a wide range of…

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Do Panels Help Solve the Purchasing Power Parity Puzzle?

面板数据有助于解决购买力平价之谜吗?

Although Rogoff described the “remarkable consensus” of 3- to 5-year half-lives of purchasing power parity (PPP) deviations among studies using long-horizon data, recent works using panel methods with post-1973 data report shorter half-lives of 2 to 2.5 years. But these studies do not use appropriate techniques to measure persistence. We extend median-unbiased estimation methods to the panel context, calculate both point estimates and confidence intervals, and provide strong…

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An Unobserved-Component Model With Switching Permanent and Transitory Innovations

永久与暂时创新切换的不可观测成分模型

This article proposes an unobserved-component model in which component innovations are governed by a state variable that follows a Markov process. The proposed model is capable of describing both stationary and nonstationary behaviors of real data and allows the random innovations to have permanent and transitory effects in different periods. The model also permits a deterministic trend with or without breaks and hence bridges the gap between the trend-stationary model and a…

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Confidence Intervals for Half-Life Deviations From Purchasing Power Parity

购买力平价偏离半衰期的置信区间

Existing point estimates of half-life deviations from purchasing power parity (PPP), around 3–5 years, suggest that the speed of convergence is extremely slow. This article assesses the degree of uncertainty around these point estimates by using local-to-unity asymptotic theory to construct confidence intervals that are robust to high persistence in small samples. The empirical evidence suggests that the lower bound of the confidence interval is between four and eight…

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A Test for Superior Predictive Ability

优越预测能力检验

We propose a new test for superior predictive ability. The new test compares favorably to the reality check (RC) for data snooping, because it is more powerful and less sensitive to poor and irrelevant alternatives. The improvements are achieved by two modifications of the RC. We use a studentized test statistic that reduces the influence of erratic forecasts and invoke a sample-dependent null distribution. The advantages of the new test are confirmed by Monte Carlo…

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