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追踪移动目标：动态贝叶斯模型的蒙特卡洛推断AI 解读

Summary Markov chain Monte Carlo (MCMC) sampling is a numerically intensive simulation technique which has greatly improved the practicality of Bayesian inference and prediction. However, MCMC sampling is too slow to be of practical use in problems involving a large number of posterior (target) distributions, as in dynamic modelling and predictive model selection. Alternative simulation techniques for tracking moving target distributions, known as particle filters, which…

有限混合模型同质性的修正似然比检验AI 解读

Summary Testing for homogeneity in finite mixture models has been investigated by many researchers. The asymptotic null distribution of the likelihood ratio test (LRT) is very complex and difficult to use in practice. We propose a modified LRT for homogeneity in finite mixture models with a general parametric kernel distribution family. The modified LRT has a χ-type of null limiting distribution and is asymptotically most powerful under local alternatives. Simulations show…

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不稳定自回归过程单位根检验的渐近分布AI 解读

UNIT ROOT TESTING has been developed through numerous papers since the work of Ž. Dickey and Fuller 1979 . The idea is to test the hypothesis that the differences of an observed time series do not depend on its levels, or in other words, the levels of the time series have a unit root that can be removed by differencing. While it is in general possible to have multiple unit roots, only the hypothesis of exactly one unit root is considered Ž. here. The available tests…

含单整时间序列的非线性回归AI 解读

An asymptotic theory is developed for nonlinear regression with integrated processes. The models allow for nonlinear effects from unit root time series and therefore deal with the case of parametric nonlinear cointegration. The theory covers integrable and asymptotically homogeneous functions. Sufficient conditions for weak consistency are given and a limit distribution theory is provided. The rates of convergence depend on the properties of the nonlinear regression…

回归不连续设计下处理效应的识别与估计AI 解读

Ž. THE REGRESSION DISCONTINUITY RD data design is a quasi-experimental design with the defining characteristic that the probability of receiving treatment changes discontinuously as a function of one or more underlying variables. This data design arises frequently in economic and other applications but is only infrequently exploited as a source of identifying information in evaluating effects of a treatment. In the first application and discussion of the RD method,…

自回归模型的自助法后再自助法预测区间AI 解读

The use of the Bonferroni prediction interval based on the bootstrap-after-bootstrap is proposed for autoregressive (AR) models. Monte Carlo simulations are conducted using a number of AR models including stationary, unit-root, and near-unit-root processes. The major finding is that the bootstrap-after-bootstrap provides a superior small-sample alternative to asymptotic and standard bootstrap prediction intervals. The latter are often too narrow, substantially…

协整向量线性约束的 Bootstrap 检验AI 解读

We consider a computer-intensive method for inference on cointegrating vectors in maximum likelihood cointegration analysis. Simulation studies show that the size distortion for the asymptotic likelihood ratio test can be considerable for small samples. Itis demonstrated that a parametric bootstrap frequently results in a nearly exact α-level test. Furthermore, response surface regression is used to examine small-sample properties of the asymptotic test. In particular, using…

预测共识的检验AI 解读

A panel of forecasts may be defined to be in consensus when individual forecasters place identical weights on a common latent variable. We suggest this definition and formulate a dynamic latent-variable model to test for consensus. This method also tests whether it is valid to use the mean forecast as the consensus forecast. In applications to surveys of U.S. macroeconomic forecasters, there is greater consensus in forecasts for output growth than for inflation or…

预测依赖估计回归参数时的预测涵盖性检验AI 解读

This article presents analytical and simulation results on the properties of two tests for forecast encompassing, allowing throughout for dependence of the forecasts on estimated regression parameters. One test, which was intended for forecasts that do not depend on regression parameters, was developed by Harvey, Leybourne, and Newbold. This test works relatively well when the size of the sample of forecast errors is very small. A second test, which explicitly accounts for…

生产中的准固定投入与长期均衡：协整分析AI 解读

Abstract This paper proposes a cointegration approach to testing the validity long‐run equilibrium in production, where capital and labour are taken as quasi‐fixed inputs. Previous studies consider only capital as the quasi‐fixed input and do not take account of the time series properties of the variables, assuming implicitly that they are stationary. The canonical cointegrating regressions (CCR) procedure is employed to test for cointegration in both the single‐equation and…

离散持续时间模型的贝叶斯半参数估计：Dirichlet 过程先验应用AI 解读

Abstract This paper proposes a Bayesian estimator for a discrete time duration model which incorporates a non‐parametric specification of the unobserved heterogeneity distribution, through the use of a Dirichlet process prior. This estimator offers distinct advantages over the Nonparametric Maximum Likelihood estimator of this model. First, it allows for exact finite sample inference. Second, it is easily estimated and mixed with flexible specifications of the baseline…

灵活需求系统函数形式的实证比较AI 解读

Abstract This paper compares the performance of eight frequently used flexible forms that are either (1) locally flexible, (2) ‘effectively globally regular’, or (3) asymptotically globally flexible. Results show that the functions with global properties generally perform better, particularly those models having asymptotic properties. Results, using US consumption data, indicate substitutability among the components of consumption at most data points. There is also some…

样本选择模型的参数与半参数估计：葡萄牙女性劳动力的实证应用AI 解读

Abstract This paper applies both parametric and semiparametric methods to the estimation of wage and participation equations for married women in Portugal. The semiparametric estimators considered are the two‐stage estimators proposed by Newey ( 1991 ) and Andrews and Schafgans ( 1998 ). The selection equation results are compared using the specification tests proposed by Horowitz ( 1993 ), Horowitz and Härdle ( 1994 ), and the wage equation results are compared using a…

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局部线性平滑的经验似然置信区间AI 解读

Empirical likelihood is considered in conjunction with the local linear smoother to construct confidence intervals for a nonparametric regression function with bounded support. The coverage error of the empirical likelihood confidence intervals is evaluated and is shown to be of the same order throughout the support of the regression function. This is a significant improvement over confidence intervals based directly on the asymptotic normal distribution of the local linear…

利用总体辅助信息的分层随机抽样经验似然推断AI 解读

The empirical likelihood method under stratified random sampling is used for making inferences on finite population parameters. Our results show that it can lead to efficient estimators by making effective use of auxiliary population information in the form of overall population totals or means ascertained from external sources. Empirical likelihood ratio confidence intervals for the population mean are also studied, and adjusted intervals with asymptotically correct…

多元分布的非参数蒙特卡洛检验AI 解读

In this paper, nonparametric Monte Carlo test procedures are proposed for composite hypotheses in which the multivariate distribution belongs to a nonparametric family. When a random variable is, in distribution, equal to a product of two independent variables, Monte Carlo simulations can be performed conditionally on one of the variables. They can be applied to testing several commonly used distributions including elliptically symmetric, reflectively symmetric,…

改进的异方差一致协方差矩阵估计量AI 解读

Este documento tem por objetivo orientar os usuários do Repositório Institucional da Universidade Federal da Bahia (RI/UFBA) quanto à conversão de arquivos para o formato PDF/A (Portable Document Format/Archive).Recomenda-se que sua produção e arquivamento sejam realizados no formato PDF/A visando assegurar o acesso e a preservação de documentos digitais a longo prazo.

利用定性约束的 bootstrap 方法降低变异性AI 解读

Parametric methods are often attractive for small to moderate samples, since, relative to nonparametric techniques, they reduce variability of a wide range of statistical procedures. However, when sample size is small there is often little empirical evidence to support a particular model, and so, while variance can be reduced, bias may be increased. In theory, smoothing can be used to reduce variability of nonparametric procedures, but the difficulty of choosing the…

双变量现状数据的关联性评估AI 解读

Assuming that the two failure times of interest with bivariate current status data follow a bivariate copula model, we propose a two‐stage estimation procedure to estimate the association parameter which is related to Kendall's tau. Asymptotic properties of the proposed semiparametric estimator show that, although the first‐stage marginal estimators have a convergence rate of only n1/3, the resulting parameter estimator still converges to a normal random variable with the…

聚类生存数据脆弱性模型中的协变量测量误差AI 解读

We propose a new class of frailty measurement error models for clustered survival data when covariates are measured with error. We show that the induced hazard function conditional on the observed covariates also follows a frailty model but of a more complicated form. We study the asymptotic bias in regression coefficients and variance components when measurement error is ignored, and the impact of censoring on this asymptotic bias. We show that the naive estimator of the…

利用二次推断函数改进广义估计方程AI 解读

Generalised estimating equations enable one to estimate regression parameters consistently in longitudinal data analysis even when the correlation structure is misspecified. However, under such misspecification, the estimator of the regression parameter can be inefficient. In this paper we introduce a method of quadratic inference functions that does not involve direct estimation of the correlation parameter, and that remains optimal even if the working correlation structure…