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含近不可逆移动平均成分模型的自助法推断AI 解读

This article proposes a bootstrap method for constructing two-sided confidence intervals for the moving average (MA) parameter in nearly noninvertible models. The confidence intervals are obtained by inverting the acceptance region of the likelihood ratio (LR) test reflecting the asymmetry of the likelihood near the noninvertibility boundary. The limiting distribution of the LR statistic is nonpivotal and its quantiles are parameterized as a function of the MA parameter and…

时间序列筛自助法的不变原理AI 解读

This paper establishes an invariance principle applicable for the asymptotic analysis of sieve bootstrap in time series. The sieve bootstrap is based on the approximation of a linear process by a finite autoregressive process of order increasing with the sample size, and resampling from the approximated autoregression. In this context, we prove an invariance principle for the bootstrap samples obtained from the approximated autoregressive process. It is of the strong form…

加性模型中交互作用的非参数估计与检验AI 解读

We consider an additive model with second-order interaction terms. Both marginal integration estimators and a combined backfitting-integration estimator are proposed for all components of the model and their derivatives. The corresponding asymptotic distributions are derived. Moreover, two test statistics for testing the presence of interactions are proposed. Asymptotics for the test functions and local power results are obtained. Because direct implementation of the test…

重复测量分析中的变系数模型与基函数近似AI 解读

A global smoothing procedure is developed using basis function approximations for estimating the parameters of a varying‐coefficient model with repeated measurements. Inference procedures based on a resampling subject bootstrap are proposed to construct confidence regions and to perform hypothesis testing. Conditional biases and variances of our estimators and their asymptotic consistency are developed explicitly. Finite sample properties of our procedures are investigated…

摘要暂缺

识别药物最低有效剂量与最高安全剂量的多重检验AI 解读

We address the problem of determining the therapeutic window of a drug by finding its minimum effective and maximum safe doses (MINED and MAXSD). The MINED is the lowest dose that exceeds the mean efficacy of the zero dose by a specified threshold, and the MAXSD is the highest dose that does not exceed the mean toxicity of the zero dose by a specified threshold. Step-down multiple test procedures are proposed to identify the MINED and MAXSD assuming a bivariate normal model.…

工具变量模型中分布处理效应的自助法检验AI 解读

This article considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) nonrandomized, but there is a binaryinstrument available for the researcher. Such a scenario is common in observational studies and in randomized experiments with imperfect compliance. One possible approach to this problem is to compare the counterfactual cumulative distribution functions of the outcome with…

An effect is attributable to treatment if it would not have been observed had the individual been exposed to control instead. Extending earlier results on attributable effects in unmatched groups, a method of exact randomization inference and sensitivity analysis is developed for case-referent, case-crossover, and cohort studies with matched sets, and a large sample approximation to the exact inference is given. The unmatched case, considered previously, has certain…

高崩溃点回归估计重抽样算法的不一致性与一种新算法AI 解读

Because high-breakdown estimators (HBEs) are impractical to compute exactly in large samples, approximate algorithms are used. The algorithm generally produces an estimator with a lower consistency rate and breakdown value than the exact theoretical estimator. This discrepancy grows with the sample size, with the implication that huge computations are needed for good approximations in large high-dimension samples. The workhorse for HBEs has been the “elemental set,” or…

依赖数据的 bootstrap 后 jackknife 方法及其一致性AI 解读

Motivated by Efron (1992, Journal of the Royal Statistical Society, Series B 54, 83–111), this paper proposes a version of the moving block jackknife as a method of estimating standard errors of block-bootstrap estimators under dependence. As in the case of independent and identically distributed (i.i.d.) observations, the proposed method merely regroups the values of a statistic from different bootstrap replicates to produce an estimate of its standard error. Consistency of…

利用鞍点近似对随机系统生存时间进行自助推断AI 解读

Summary The single bootstrap is implemented by using a saddlepoint approximation to determine estimates for the survival and hazard functions of first-passage times in complicated semi-Markov processes. The double bootstrap is also implemented by resampling saddlepoint inversions and provides BCa confidence bands for these functions. Confidence intervals for the mean and variance of first-passage times are easily computed. A new characterization of the asymptotic hazard rate…

摘要暂缺

极值估计量的计算便捷型 k 步 Bootstrap 的高阶改进AI 解读

The copyright to this Article is held by the Econometric Society. It may be downloaded, printed and reproduced only for educational or research purposes, including use in course packs. No downloading or copying may be done for any commercial purpose without the explicit permission of the Econometric Society. For such commercial purposes contact the Office of the Econometric Society (contact information may be found at the website

向量自回归与现实AI 解读

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…

病例对照数据逻辑回归模型的信息矩阵检验AI 解读

We propose an information‐matrix‐based goodness‐of‐fit statistic to test the validity of the logistic regression model based on case‐control data by extending the information matrix test of White (1982) for detecting one‐sample parametric model misspecification to the semiparametric profile likelihood setting under a two‐sample semiparametric model, which is equivalent to the assumed logistic regression model. The proposed test statistic requires a high‐dimensional matrix…

簇内重抽样AI 解读

Within‐cluster resampling is proposed as a new method for analysing clustered data. Although the focus of this paper is clustered binary data, the within‐cluster resampling asymptotic theory is general for many types of clustered data. Within‐cluster resampling is a simple but computationally intensive estimation method. Its main advantage over other marginal analysis methods, such as generalised estimating equations (Liang & Zeger, 1986; Zeger & Liang, 1986) is that it…

渐消加权区块自助法AI 解读

We introduce and study tapered block bootstrap methodology that yields an improvement over the well‐known block bootstrap for time series of Künsch (1989). The asymptotic validity and the favourable bias properties of the tapered block bootstrap are shown. The important practical issues of optimally choosing the window shape and the block size are addressed in detail, while some finite‐sample simulations are presented validating the good performance of the tapered block…

群组随机试验分析的最优置换检验AI 解读

Two facts complicate the comparison of interventions in group randomized trials (GRT's), a family of clinical trials in which each member of a particular group receives the same treatment assignment. First, individual outcomes within each group are often correlated. Second, the number of groups in a GRT is often not sufficient to make asymptotic approximations possible. Therefore, the tests used with methods, such as generalized estimating equations (GEE) and penalized quasi…

提高非参数预测区间的覆盖准确性AI 解读

Summary Methods are suggested for improving the coverage accuracy of intervals for predicting future values of a random variable drawn from a sampled distribution. It is shown that properties of solutions to such problems may be quite unexpected. For example, the bootstrap and the jackknife perform very poorly when used to calibrate coverage, although the jackknife estimator of the true coverage is virtually unbiased. A version of the smoothed bootstrap can be employed for…

含单位根的门槛自回归模型AI 解读

This paper develops an asymptotic theory of inference for an unrestricted two-regime threshold autoregressive (TAR) model with an autoregressive unit root. We find that the asymptotic null distribution of Wald tests for a threshold are nonstandard and different from the stationary case, and suggest basing inference on a bootstrap approximation. We also study the asymptotic null distributions of tests for an autoregressive unit root, and find that they are nonstandard and…

可预测性的度量：理论与宏观经济应用AI 解读

Abstract We propose a measure of predictability based on the ratio of the expected loss of a short‐run forecast to the expected loss of a long‐run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or multivariate information sets, and covariance stationary or difference stationary processes. We propose a simple estimator, and we suggest resampling methods for inference. We then…

基于自助法的非参数回归显著性检验AI 解读

This paper proposes a test for selecting explanatory variables in nonparametric regression. The test does not need to estimate the conditional expectation function given all the variables, but only those which are significant under the null hypothesis. This feature is computationally convenient and solves, in part, the problem of the “curse of dimensionality” when selecting regressors in a nonparametric context. The proposed test statistic is based on functionals of a $U$-pro…

非参数协方差分析AI 解读

In the problem of testing the equalityof k regression curves from independent samples, we discuss three methods using nonparametric estimators of the regression function. The first test is based on a linear combination of estimators for the integrated variance function in the individual samples and in the combined sample. The second approach transfers the classical one-way analysis of variance to the situation of comparing non-parametric curves, while the third test compares…

We examine the way in which empirical bandwidth choice affects distributional properties of nonparametric density estimators. Two bandwidth selection methods are considered in detail: local and global plug-in rules. Particular attention is focussed on whether the accuracy of distributional bootstrap approximations is appreciably influenced by using the resample version $\hat{h}*$,rather than the sample version $\hat{h}$, of an empirical bandwidth. It is shown theoretically…