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随机设计非参数回归的渐近等价理论AI 解读

This paper establishes the global asymptotic equivalence between the nonparametric regression with random design and the white noise under sharp smoothness conditions on an unknown regression or drift function. The asymptotic equivalence is established by constructing explicit equivalence mappings between the nonparametric regression and the white-noise experiments, which provide synthetic observations and synthetic asymptotic solutions from any one of the two experiments…

Poisson 强度估计与正漂移扩散估计的渐近等价性AI 解读

We consider a diffusion model of small variance type with positive drift density varying in a nonparametric set. We investigate Gaussian and Poisson approximations to this model in the sense of asymptotic equivalence of experiments. It is shown that observation of the diffusion process until its first hitting time of level one is a natural model for the purpose of inference on the drift density. The diffusion model can be discretized by the collection of level crossing times…

Hildreth–Houck 随机系数模型的极大似然估计AI 解读

We explore maximum likelihood (ML) estimation of the Hildreth-Houck random coefficients model. We show that the global ML estimator can be inconsistent. We develop an alternative LML (local ML) estimator and prove that it is consistent and asymptotically efficient for points in the interior of the parameters. Properties of the LML and comparisons with common method of moments (MM) estimates are done via Monte Carlo. Boundary parameters lead to nonstandard asymptotic…

This paper studies the error in forecasting an autoregressive process with a deterministic component. We show that when the data are strongly serially correlated, forecasts based on a model that detrends the data using OLS before estimating the autoregressive parameters are much less precise than those based on an autoregression that includes the deterministic components, and the asymptotic distribution of the forecast errors under the two‐step procedure exhibits bimodality.…

In this paper the application of the score principle to test for unit roots in seasonal processes is analysed. In particular, tests based on the procedure proposed by Hylleberg et al.(1990, Journal of Econometrics, 44, 215–38) (HEGY) are introduced and the respective limit distributions derived in a local‐to‐unity context. It is shown that these statistics converge to distributions already tabulated in the literature. A Monte Carlo investigation contrasting the conventional…

In this paper, we define and study a new block bootstrap variation, the taperedblock bootstrap, that is applicable in the general case of approximately linear statistics, and constitutes an improvement over the original block bootstrap of Künsch (1989). The asymptotic validity, and the favorable bias properties of the tapered block bootstrap are shown in two important cases: smooth functions of means, and M‐estimators. The important practical issues of optimally choosing the…

非线性动态模型的模型选择检验AI 解读

This paper generalizes Vuong (1989) asymptotically normal tests for model selection in several important directions. First, it allows for incompletely parametrized models such as econometric models defined by moment conditions. Second, it allows for a broad class of estimation methods that includes most estimators currently used in practice. Third, it considers model selection criteria other than the models" likelihoods such as the mean squared errors of prediction. Fourth,…

利用经验似然检验线性模型中的线性约束AI 解读

In this paper we analyse the higher order asymptotic behaviour of a profiled empirical likelihood ratio which can be used to test a set of linear restrictions in linear regression models. We show that the resulting profiled empirical likelihood ratio admits a Bartlett correction which can be used to improve to third order the accuracy of commonly used tests in applied research without any distributional assumptions about the error process. Copyright Royal Economic Society…

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用于时间序列拟合不足诊断的综合检验AI 解读

A new portmanteau test for time series, more powerful than the tests of Ljung and Box and Monti, is proposed. The test is based on the mth root of the determinant of the mth autocorrelation matrix. It is shown that the proposed statistic is a function of all of the squared multiple correlation coefficients of the regressions of the residuals on their lags when the number of lags goes from 1 to m. It can also be written as a function of the first m partial autocorrelation…

Cox回归中缺失协变量的双半参数方法AI 解读

The problem of nuisance covariate model specification is considered in Cox regression where the maximum semiparametric likelihood method is used to handle the missing covariates. A component of the covariates is modeled nonparametrically to achieve robustness against covariate model misspecification and to reduce the number of possibly intractable integrations involved in the parametric modeling of the covariates. The statistical properties of the proposed method are…

聚类失效时间数据的半参数混合效应模型AI 解读

The Cox proportional hazards model with a random effect has been proposed for the analysis of data which consist of a large number of small clusters of correlated failure time observations. The class of linear transformation models provides many useful alternatives to the Cox model for analyzing univariate failure time data. In this article, we generalize these models by incorporating random effects, which generate the dependence among the failure times within the cluster,…

利用多尺度最大似然检测混合分布AI 解读

A test of homogeneity tries to decide whether observations come from a single distribution or from a mixture of several distributions. A powerful theory has been developed for the case where the component distributions are members of an exponential family. When no parametric assumptions are appropriate, the standard approach is to test for bimodality, which is known not to be very sensitive for detecting heterogeneity. To develop a more sensitive procedure, this article…

通过复变量模拟外推进行校正得分估计AI 解读

A Monte Carlo method of computing unbiased estimating equations for the analysis of data measured with error is described. Asymptotic distribution results are obtained for estimators derived from the Monte Carlo estimating equations. The method is illustrated with examples, applications, and simulation studies. The Monte Carlo estimating equations are corrected scores in the sense of Nakamura, and the proposed methods are closely related to the simulation method described by…

平稳类别时间序列的可变长度马尔可夫链筛自助法AI 解读

A bootstrap for stationary categorical time series based on the method of sieves is studied here. The data-generating process is approximated by the so-called variable-length Markov chain (VLMC), a flexible class of Markov models that allows for parsimonious structure. Then the resampling is given by simulating from the fitted model. It is shown that for a whole class of stationary categorical time series that is more general than VLMC, the VLMC sieve has faster rate of…

含非期望产出的多产出生产模型AI 解读

Many production processes yield both good outputs and undesirable ones (e.g., pollutants). In this article we develop a generalization of a stochastic frontier model that is appropriate for such technologies. We discuss efficiency analysis and, in particular, define technical and environmental efficiency in the context of our model. We develop methods for carrying out Bayesian inference and apply them to a panel data set of Dutch dairy farms, where excess nitrogen production…

潜变量层级模型中的经验贝叶斯与题目聚类效应AI 解读

Empirical Bayes regression procedures are often used in educational and psychological testing as extensions to latent variables models. The National Assessment of Educational Progress (NAEP) is an important national survey using such procedures. The NAEP applies empirical Bayes methods to models from item response theory to calibrate student responses to questions of varying difficulty. Due partially to the limited computing technology that existed when NAEP was first…

与表型相关的基因区域异质性非参数检验AI 解读

High-dimensional statistical problems arise in the investigation of the relationship between reduced sensitivity to antiretroviral drugs among human immunodeficiency virus-infected patients and viral genotypic patterns obtained from blood samples. This article develops a nonparametric approach for analyzing gene region heterogeneity associated with drug-resistance phenotype. The method is based on the distribution of distances between viral genetic sequences. The distance…

可忽略性不确定下的小区域二元数据分层贝叶斯无响应模型AI 解读

In the National Crime Survey (NCS), data on victimization can be poststratified into domains determined by urbanization, type of place, and poverty level. There is much difficulty in the analysis of binary data with substantial nonresponse. We consider three Bayesian hierarchical models for binary nonresponse data, like those from the NCS, which are clustered within a number of domains or areas. As in small area estimation, one key feature is that each model “borrows…

ABSTRACT We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that range‐based volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence range‐based Gaussian quasi‐maximum likelihood estimation produces highly efficient estimates of stochastic volatility models and extractions of latent volatility. We use our method to examine…

阈值模型最小绝对偏差估计的说明AI 解读

This paper develops the limit law for the least absolute deviation estimator of the threshold parameter in linear regression. In this respect, we extend the literature of threshold models. The existing literature considers only the least squares estimation of the threshold parameter (see Chan, 1993, Annals of Statistics 21, 520–533; Hansen, 2000, Econometrica 68, 575–605). This result is useful because in the case of heavy-tailed errors there is an efficiency loss resulting…