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实数空间上不规则间隔数据的傅里叶分析AI 解读

Summary The purpose of the paper is to propose a frequency domain approach for irregularly spaced data on Rd. We extend the original definition of a periodogram for time series to that for irregularly spaced data and define non-parametric and parametric spectral density estimators in a way that is similar to the classical approach. Introduction of the mixed asymptotics, which are one of the asymptotics for irregularly spaced data, makes it possible to provide asymptotic…

一类新的二元联合尾部模型AI 解读

Summary A fundamental issue in applied multivariate extreme value analysis is modelling dependence within joint tail regions. The primary focus of this work is to extend the classical pseudopolar treatment of multivariate extremes to develop an asymptotically motivated representation of extremal dependence that also encompasses asymptotic independence. Starting with the usual mild bivariate regular variation assumptions that underpin the coefficient of tail dependence as a…

随机删失结果的分布处理效应非参数检验AI 解读

Summary For a binary treatment ν = 0, 1 and the corresponding ‘potential response’Y0 for the control group (ν = 0) and Y1 for the treatment group (ν = 1), one definition of no treatment effect is that Y0 and Y1 follow the same distribution given a covariate vector X. Koul and Schick have provided a non-parametric test for no distributional effect when the realized response (1−ν)Y0+νY1 is fully observed and the distribution of X is the same across the two groups. This test is…

调制更新过程模型的伪鞅估计方程AI 解读

Summary We adapt martingale estimating equations based on gap time information to a general intensity model for a single realization of a modulated renewal process. The consistency and asymptotic normality of the estimators is proved under ergodicity conditions. Previous work has considered either parametric likelihood analysis or semiparametric multiplicative models using partial likelihood. The framework is generally applicable to semiparametric and parametric models,…

同时收缩均值与方差的经验贝叶斯置信区间AI 解读

Summary We construct empirical Bayes intervals for a large number p of means. The existing intervals in the literature assume that variances σi2 are either equal or unequal but known. When the variances are unequal and unknown, the suggestion is typically to replace them by unbiased estimators Si2. However, when p is large, there would be advantage in ‘borrowing strength’ from each other. We derive double-shrinkage intervals for means on the basis of our empirical Bayes…

非参数单调函数估计的贝叶斯方法AI 解读

Summary The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first approach uses a hierarchical Bayes framework and a characterization of smooth monotone functions given by Ramsay that allows unconstrained estimation. The second approach uses a Bayesian regression spline model of Smith and Kohn with a mixture distribution of constrained normal distributions as the prior for the regression coefficients to ensure the monotonicity of…

利用检验统计量进行贝叶斯模型选择AI 解读

Summary Existing Bayesian model selection procedures require the specification of prior distributions on the parameters appearing in every model in the selection set. In practice, this requirement limits the application of Bayesian model selection methodology. To overcome this limitation, we propose a new approach towards Bayesian model selection that uses classical test statistics to compute Bayes factors between possible models. In several test cases, our approach produces…

估计方程框架下纵向数据的一致模型选择与数据驱动光滑检验AI 解读

Summary Model selection for marginal regression analysis of longitudinal data is challenging owing to the presence of correlation and the difficulty of specifying the full likelihood, particularly for correlated categorical data. The paper introduces a novel Bayesian information criterion type model selection procedure based on the quadratic inference function, which does not require the full likelihood or quasi-likelihood. With probability approaching 1, the criterion…

逆回归中的失拟检验及其生物光子成像应用AI 解读

Summary We propose two test statistics for use in inverse regression problems Y = Kθ+ε, where K is a given linear operator which cannot be continuously inverted. Thus, only noisy, indirect observations Y for the function θ are available. Both test statistics have a counterpart in classical hypothesis testing, where they are called the order selection test and the data-driven Neyman smooth test. We also introduce two model selection criteria which extend the classical Akaike…

含交互作用的半参数模型检验及基因—环境交互应用AI 解读

Summary Motivated from the problem of testing for genetic effects on complex traits in the presence of gene–environment interaction, we develop score tests in general semiparametric regression problems that involves Tukey style 1 degree-of-freedom form of interaction between parametrically and non-parametrically modelled covariates. We find that the score test in this type of model, as recently developed by Chatterjee and co-workers in the fully parametric setting, is biased…

DASSO：Dantzig 选择器与 Lasso 的联系AI 解读

Summary We propose a new algorithm, DASSO, for fitting the entire coefficient path of the Dantzig selector with a similar computational cost to the least angle regression algorithm that is used to compute the lasso. DASSO efficiently constructs a piecewise linear path through a sequential simplex-like algorithm, which is remarkably similar to the least angle regression algorithm. Comparison of the two algorithms sheds new light on the question of how the lasso and Dantzig…

非对称指数幂分布的性质与估计AI 解读

The new distribution class, Asymmetric Exponential Power Distribution (AEPD), proposed in this paper generalizes the class of Skewed Exponential Power Distributions (SEPD) in a way that in addition to skewness introduces different decay rates of density in the left and right tails. Our parametrization provides an interpretable role for each parameter. We derive moments and moment-based measures: skewness, kurtosis, expected shortfall. It is demonstrated that a maximum…

具有社会互动的同步博弈中的统计推断AI 解读

This paper studies inference in a continuous time game where an agent's decision to quit an activity depends on the participation of other players. In equilibrium, similar actions can be explained not only by direct influences but also by correlated factors. Our model can be seen as a simultaneous duration model with multiple decision makers and interdependent durations. We study the problem of determining the existence and uniqueness of equilibrium stopping strategies in…

具有单调功效的均值变化检验AI 解读

Several widely used tests for a changing mean exhibit nonmonotonic power in finite samples, due to "incorrect"Â estimation of nuisance parameters under the alternative. In this paper, we study the issue of nonmonotonic power in testing for changing mean. We investigate the asymptotic power properties of the tests, using a new framework where alternatives are characterized as having "large" changes. The asymptotic analysis provides a theoretical explanation to the power…

零假设与备择下均允许未知时点趋势突变的单位根检验AI 解读

Perron [Perron, P., 1989. The great crash, the oil price shock and the unit root hypothesis. Econometrica 57, 1361-1401] introduced a variety of unit root tests that are valid when a break in the trend function of a time series is present. The motivation was to devise testing procedures that were invariant to the magnitude of the shift in level and/or slope. In particular, if a change is present it is allowed under both the null and alternative hypotheses. This analysis was…

部分不稳定广义矩模型中的有效推断AI 解读

This paper considers time series Generalized Method of Moments (GMM) models where a subset of the parameters are time varying. We focus on an empirically relevant case with moderately large instabilities, which are well approximated by a local asymptotic embedding that does not allow the instability to be detected with certainty, even in the limit. We show that for many forms of the instability and a large class of GMM models, usual GMM inference on the subset of stable…

条件不相关性检验AI 解读

We propose a nonparametric test for conditional uncorrelatedness in multiple-equation models such as seemingly unrelated regressions (SURs), multivariate volatility models, and vector autoregressions (VARs). Under the null hypothesis of conditional uncorrelatedness, the test statistic converges to the standard normal distribution asymptotically. We also study the local power property of the test. Simulation shows that the test behaves quite well in finite samples.

非线性价格下水需求的简约式模型与结构模型比较AI 解读

Increasing-block prices are common in markets for water, cellular phone service, and retail electricity. This study estimates demand models under block prices and conducts a Monte Carlo experiment to test the small-sample bias of structural and instrumental variables (IV) estimators. We estimate the price and income elasticity of water demand under increasing-block prices using a structural discrete/continuous choice (DCC) model, as well as random effects and IV. Elasticity…

不平等、贫困与福利的广义基尼指数统计推断AI 解读

This article considers statistical inference for consistent estimators of generalized Gini indices of inequality, poverty, and welfare. Our method does not require grouping the population into a fixed number of quantiles. The empirical indices are shown to be asymptotically normally distributed using functional limit theory. Easily computed asymptotic variance expressions are obtained using influence functions. Inference based on first-order asymptotics is then compared with…

国际产出趋同：来自自相关函数方法的证据AI 解读

Abstract This paper uses an autocorrelation function (ACF) approach to develop a new testing procedure for international output convergence. We define convergence in terms of sample ACFs of detrended output per capita, and construct an inference set‐up based on resampling and subsampling techniques for dependent data. Using per capita GDP for 15 OECD countries observed over a century, we find that the hypothesis of conditional convergence is unsupported; that, the USA apart,…

未知异方差与非线性依赖下线性中位数回归的有限样本无分布推断AI 解读

We construct finite-sample distribution-free tests and confidence sets for the parameters of a linear median regression, where no parametric assumption is imposed on the noise distribution. The set-up studied allows for non-normality, heteroscedasticity, non-linear serial dependence of unknown forms as well as for discrete distributions. We consider a mediangale structure--the median-based analogue of a martingale difference--and show that the signs of mediangale sequences…

矩不等式置信区间端点的自助法与 m out of n 自助法失效AI 解读

This paper analyses the finite-sample and asymptotic properties of several bootstrap and m out of n bootstrap methods for constructing confidence interval (CI) endpoints in models defined by moment inequalities. In particular, we consider using these methods directly to construct CI endpoints. By considering two very simple models, the paper shows that neither the bootstrap nor the m out of n bootstrap is valid in finite samples or in a uniform asymptotic sense in general…

样本选择模型的两步级数估计AI 解读

Sample selection models are important for correcting the effects of non-random sampling. This paper is about semiparametric estimation using a series approximation to the correction term. Regression spline and power series approximations are considered. Asymptotic normality and consistency of an asymptotic variance estimator are shown. Copyright (C) The Author(s). Journal compilation (C) Royal Economic Society 2009

动态线性模型的分布无关设定检验AI 解读

-process of the residuals. This transformation approximates the martingale component of the process so that it converges weakly to the standard Brownian motion under the null hypothesis. One feature of our setup is that we do not require to specify the dynamic structure of the regressors. Due to this, the transformation employs a semi-parametric correction that does not restrict the class of local alternatives that our tests can detect, in contrast with other works using…