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考虑有效持续时间变化的重复测量治疗效应估计AI 解读

To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness…

扩展常规先验以检验线性模型中的一般假设AI 解读

We consider that observations come from a general normal linear model and that it is desirable to test a simplifying null hypothesis about the parameters. We approach this problem from an objective Bayesian, model-selection perspective. Crucial ingredients for this approach are ‘proper objective priors’ to be used for deriving the Bayes factors. Jeffreys-Zellner-Siow priors have good properties for testing null hypotheses defined by specific values of the parameters in…

未知形式条件异方差下时间序列条件均值模型的改进广义谱检验AI 解读

Dynamic economic theories usually have implications on and only on the conditional mean dynamics of economic processes. Using a generalized spectral derivative approach, Hong and Lee (2005, Review of Economic Studies 72, 499–541) recently proposed a new class of omnibus nonparametric specification tests for linear and nonlinear time series conditional mean models, where the dimension of the conditioning information set may be infinite. The tests can detect a wide range of…

摘要暂缺

协同结构突变（Co-breaking）AI 解读

This article has two aims. First, we provide a synopsis of the literature on co-breaking that has developed in several, seemingly disconnected, strands. We establish a consistent terminology, collect theoretical results, delimit co-breaking to cointegration and common features, and review recent contributions to co-breaking regressions and the budding analysis of co-breaking rank. Second, we present new results in the field, particularly, on the importance of co-breaking for…

高斯局部平稳过程的非参数准最大似然估计AI 解读

This paper deals with nonparametric maximum likelihood estimation for Gaussian locally stationary processes. Our nonparametric MLE is constructed by minimizing a frequency domain likelihood over a class of functions. The asymptotic behavior of the resulting estimator is studied. The results depend on the richness of the class of functions. Both sieve estimation and global estimation are considered. Our results apply, in particular, to estimation under shape constraints. As…

广泛依赖误差下平稳性对趋势与单位根的检验AI 解读

We suggest a rescaled variance type of test for the null hypothesis of stationarity against deterministic and stochastic trends (unit roots). The deterministic trend can be represented as a general function in time (e.g., nonparametric, linear, or polynomial regression, abrupt changes in the mean). Under the null, the asymptotic distribution of the test is derived, and critical values are tabulated for a wide class of stationary processes with short, long, or negative…

局部平稳过程的模型选择与半参数估计AI 解读

Summary Over recent decades increasingly more attention has been paid to the problem of how to fit a parametric model of time series with time-varying parameters. A typical example is given by autoregressive models with time-varying parameters. We propose a procedure to fit such time-varying models to general non-stationary processes. The estimator is a maximum Whittle likelihood estimator on sieves. The results do not assume that the observed process belongs to a specific…

确定门限自回归模型状态数的序贯程序AI 解读

In this paper, we propose a sequential method for determining the number of regimes in threshold autoregressive models. The proposed method relies on the superconsistency of sequential threshold estimates and uses general linearity tests to determine the number of thresholds. A simulation study is performed in order to find out the finite-sample properties of our procedure and to compare it with two other procedures available in the literature. We find that our method works…

电价的状态转换长记忆模型AI 解读

In this paper we develop a regime switching model which can generate long memory (fractional integration) in each of the regime states. This property is relevant in a number of cases. For instance, the deregulated market for electricity power in the Nordic countries is characterized by electricity spot prices with a high degree of long memory. It occurs that in some time periods bilateral prices are identical whereas in other periods the prices differ. The latter occurs when…

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回归系数一般持续性时变的有效检验AI 解读

There are a large number of tests for instability or breaks in coefficients in regression models designed for different possible departures from the stable model. We make two contributions to this literature. First, we consider a large class of persistent breaking processes that lead to asymptotically equivalent efficient tests. Our class allows for many or relatively few breaks, clustered breaks, regularly occurring breaks, or smooth transitions to changes in the regression…

短时段内协整关系失效的检验AI 解读

This article introduces tests for cointegration breakdown that may occur over a relatively short time period, such as at the end of the sample. The breakdown may be due to a shift in the cointegrating vector or due to a shift in the errors from being I(0) to being I(1). Tests are introduced based on the postbreakdown sum of squared residuals and sum of squared reverse partial sums of residuals. Critical values are provided using a subsampling method. Asymptotic results take…

计数过程半参数变换模型的有效估计AI 解读

A class of semiparametric transformation models is proposed to characterise the effects of possibly time-varying covariates on the intensity functions of counting processes. The class includes the proportional intensity model and linear transformation models as special cases. Nonparametric maximum likelihood estimators are developed for the regression parameters and cumulative intensity functions of these models based on censored data. The estimators are shown to be…

演化小波谱的 Haar–Fisz 估计AI 解读

Summary We propose a new ‘Haar–Fisz’ technique for estimating the time-varying, piecewise constant local variance of a locally stationary Gaussian time series. We apply our technique to the estimation of the spectral structure in the locally stationary wavelet model. Our method combines Haar wavelets and the variance stabilizing Fisz transform. The resulting estimator is mean square consistent, rapidly computable and easy to implement, and performs well in practice. We also…

用边际积分估计和检验加性模型中的变系数AI 解读

We propose marginal integration estimation and testing methods for the coefficients of varying-coefficient multivariate regression models. Asymptotic distribution theory is developed for the estimation method, which enjoys the same rate of convergence as univariate function estimation. For the test statistic, asymptotic normal theory is established. These theoretical results are derived under the fairly general conditions of absolute regularity (β-mixing). Application of the…

地理加性生存模型AI 解读

Survival data often contain small-area geographical or spatial information, such as the residence of individuals. In many cases, the impact of such spatial effects on hazard rates is of considerable substantive interest. Therefore, extensions of known survival or hazard rate models to spatial models have been suggested. Mostly, a spatial component is added to the usual linear predictor of the Cox model. In this article flexible continuous-time geoadditive models are…

基于德国数据的欧元区小型货币系统AI 解读

Abstract Previous euro area money demand studies have used aggregated national time series data from the countries participating in the European Monetary Union (EMU). However, aggregation may be problematic because macroeconomic convergence processes have taken place in the countries of interest. Therefore, in this study, quarterly German data until 1998 are combined with data from the euro area from 1999 until 2002 and these series are used for fitting a small vector error…

初始观测来自无条件分布时的单位根检验与结构变化AI 解读

Following Elliott (1999; International Economic Review 40, 767--83.) and Perron and Rodríguez (2003; Journal of Econometrics 115,1--27), we develop unit root tests in the context of structural change models using GLS detrended data ( Elliott, Rothenberg and Stock 1996; Econometrica 64, 813--39) when the initial observation is drawn from its unconditional distribution. We derive the limiting distributions of the M-tests ( Stock, 1999 cointegration, causality and forecasting;…

含结构突变的单位根检验：联合假设的设定AI 解读

Several tests based on a t-ratio have been proposed in the literature to decide the order of integration of a time series allowing for a structural break. However, another approach based on testing a joint hypothesis of unit root and the irrelevance of some nuisance parameters is also feasible. This paper proposes new unit root tests consistent with the presence of a structural break applying this second perspective. Our approach deals both with the case where the break is…

摘要暂缺

基于 Wishart 过程的多变量随机波动率模型AI 解读

Financial models for asset and derivatives pricing, risk management, portfolio optimization, and asset allocation rely on volatility forecasts. Time-varying volatility models, such as generalized autoregressive conditional heteroscedasticity and stochastic volatility (SVOL), have been successful in improving forecasts over constant volatility models. We develop a new multivariate SVOL framework for modeling financial data that assumes covariance matrices stochastically…

含内生时变协变量的不完整泊松数据的条件推断方法AI 解读

We investigate the effect of protease inhibitors (PIs) on the rate of emergency room (ER) visits among HIV-infected women from a longitudinal cohort study. One strategy for accounting for serial correlation in longitudinal studies is to assume that observations are independent, conditional on unit-specific nuisance parameters. It is possible to estimate these models using unconditional maximum likelihood, where the nuisance parameters are assigned a parametric distribution…

区分长程依赖与均值变化AI 解读

We develop a testing procedure for distinguishing between a long-range dependent time series and a weakly dependent time series with change-points in the mean. In the simplest case, under the null hypothesis the time series is weakly dependent with one change in mean at an unknown point, and under the alternative it is long-range dependent. We compute the CUSUM statistic Tn, which allows us to construct an estimator k̂ of a change-point. We then compute the statistic Tn,1…