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参数恒定性的 MOSUM 检验AI 解读

In this paper, tests for structural change based on moving sums (MOSUMS) of recursive and least-squares residuals are investigated. We obtain and tabulate the asymptotic critical values of the MOSUM test with recursive residuals and show that the asymptotic critical values of the MOSUM test with least-squares residuals can easily be obtained from already existing tables for the moving-estimates test. We also show that these MOSUM tests are consistent and have nontrivial…

投影偏似然及其在纵向数据中的应用AI 解读

An estimating equation, which we call the projected partial score, is introduced for longitudinal data analysis. The estimating equation is obtained by projecting the partial likelihood score function onto the vector space spanned by a class of ‘conditionally linear’ estimating equations. We demonstrate that removing certain terms from the projection of the full likelihood score does not alter important inferential properties of the estimating equation, and doing so is…

ARMA模型残差序贯经验过程的弱收敛AI 解读

This paper studies the weak convergence of the sequential empirical process $\widehat{K}_n$ of the estimated residuals in ARMA$(p, q)$ models when the errors are independent and identically distributed. It is shown that, under some mild conditions, $\widehat{K}_n$ converges weakly to a Kiefer process. The weak convergence is discussed for both finite and infinite variance time series models. An application to a change-point problem is considered.

结构变化模型中的单位根检验AI 解读

This paper considers the unit root tests in models with structural change. Particular attention is given to their dependency on the limiting ratios of the subsample sizes between breaks. The dependency is analyzed in detail, and the invariant testing procedure based on a transformed model is developed. The required transformation is essentially identical to the generalized least-squares correction for heteroskedasticity. The limiting distributions of the new tests do not…

通过统计推断评价真实经济周期模型：法国数据应用AI 解读

The aim of this paper is to evaluate the capacity of RBC models to mimic the French business cycle. We are thus led to investigate the three following assumptions on the labour market: (1) the non-time separability of leisure, (2) the indivisibility of labour and (3) the imperfect information on labour market and time-varying effort. Using the General Method of Moments, we estimate the structural parameters and we test (1) the model's hypothesis using a set of…

干扰参数仅在备择假设下存在时的最优检验AI 解读

This paper derives asymptotically optimal tests for testing problems in which a nuisance parameter exists under the alternative hypothesis but not under the null. For example, the results apply to tests of structural change with unknown changepoint. The testing problem considered is nonstandard and the classical asymptotic optimality results for the Lagrange multiplier, Wald, and likelihood ratio do not apply. A weighted average power criterion is used here to generate…

动态模型的最优递归估计AI 解读

This article checks, using both real and simulated data, the effectiveness of modern adaptive techniques to track the parameters of time-varying dynamic models. The real case studies concern a bone marrow transplant data set published by Tong, the gas furnace model of Box and Jenkins, and two series of West German interest rates. Simulation studies focus on ARX models with smoothly and suddenly changing parameters. The general approach is to compare the fitting-forecasting…

利用平方累积和回顾检测方差变化AI 解读

This article studies the problem of multiple change points in the variance of a sequence of independent observations. We propose a procedure to detect variance changes based on an iterated cumulative sums of squares (ICSS) algorithm. We study the properties of the centered cumulative sum of squares function and give an intuitive basis for the ICSS algorithm. For series of moderate size (i.e., 200 observations and beyond), the ICSS algorithm offers results comparable to those…

动态模型的最优递归估计AI 解读

This article checks, using both real and simulated data, the effectiveness of modern adaptive techniques to track the parameters of time-varying dynamic models. The real case studies concern a bone marrow transplant data set published by Tong, the gas furnace model of Box and Jenkins, and two series of West German interest rates. Simulation studies focus on ARX models with smoothly and suddenly changing parameters. The general approach is to compare the fitting-forecasting…

扫描统计量检测伯努利序列变化区段的功效AI 解读

Fu & Curnow (1990) derive recursive equations to find the level of significance and power of a likelihood ratio test for a changed segment of specified length, based on the scan statistic, the maximum number of successes within the specified length. Their method is computationally feasible for segment lengths of 20 or less. We present and evaluate highly accurate approximations as well as bounds for the power function of this test that are computationally feasible even for…

结合数据驱动模型选择的单位根后验赔率检验AI 解读

The Kalman filter is used to derive updating equations for the Bayesian data density in discrete time linear regression models with stochastic regressors. The implied “Bayes model” has time varying parameters and conditionally heterogeneous error variances. A σ-finite Bayes model measure is given and used to produce a new-model-selection criterion (PIC) and objective posterior odds tests for sharp null hypotheses like the presence of a unit root. This extends earlier work by…

趋势平稳与差分平稳的贝叶斯推断AI 解读

This paper proposes a general Bayesian framework for distinguishing between trend- and difference-stationarity. Usually, in model selection, we assume that all of the data were generated by one of the models under consideration. In studying time series, however, we may be concerned that the process is changing over time, so that the preferred model changes over time as well. To handle this possibility, we compute the posterior probabilities of the competing models for each…

经济时间序列的贝叶斯预测AI 解读

A model is suggested to forecast economic time series. This model incorporates some innovative ideas of Harrison and Stevens [20] for building into the forecasting process important external shocks to the systems. Thus the occurrence of possibly significant real-world events may cause a fundamental change in the time series in question. The Jeffreys-Savage (JS) Bayesian theory of hypothesis testing is used to test the hypothesis that a particular event has been such as to…

经济周期阶段及其转移动态AI 解读

This article examines differences in expansionary and contractionary phases of the business cycle. By extending the nonlinear Markov-switching estimation method of J. D. Hamilton to incorporate time-varying probabilities of transitions between the phases, the marginal benefits of the time-varying transition probability Markov-switching model are highlighted. Using this technique, the author documents the high correlation between the evolution of the phases inferred from the…

存在未观测异质性时的比例风险假设检验AI 解读

Abstract This paper develops a discrete‐time hazard model which accounts for unmeasured hetergeneity while allowing the coefficients of the regressors to vary over time. Sufficient conditions for nonparametric identifiability of the unmeasured heterogeneity distribution are derived. Testing for time‐varying coefficients in this model is, under suitable conditions, equivalent to testing the proportionality assumption of the underlying continuous‐time hazard model. Some Monte…

变点问题中的线性估计量AI 解读

Observations $X_i$ are uncorrelated with means $\theta_i, i = 1,\cdots, n$, and variances 1. The linear estimators $\widehat{\theta} = T\mathbf{X}$, for some $n \times n$ matrix $T$, are widely used in smoothing problems, where it is assumed that neighbouring parameter values are similar. The smoothness assumption is violated in change point problems, where neighbouring parameter values are equal, except at some unspecified change points where there are jumps of unknown size…

分布变化检测的高效序贯非参数方案AI 解读

Suppose that a system in its standard state produces i.i.d. observations whose distribution is symmetric about zero. At an unknown time the system may leave its standard state, and the observations would subsequently be stochastically larger. Subject to a bound on the rate of false alarms, one wants to detect quickly such a departure from the standard state. We present a robust method of detection which is computationally feasible and remarkably efficient. The method is…

This paper describes a dynamic or state-space approach for analyzing discrete time or grouped survival data. Simultaneous estimation of baseline hazard functions and of time-varying covariate effects is based on maximization of posterior densities or, equivalently, a penalized likelihood, leading to Kalman-type smoothing algorithms. Data-driven choice of unknown smoothing parameters is possible via an EM-type procedure. The methods are illustrated by applications to real…

摘要暂缺

扩散过程离散观测的贝叶斯因子AI 解读

We present an approach to model selection for a time series of data on a fine time scale. The underlying process generating the data is modelled as a continuous time stochastic process. The underlying continuous processes are assumed to be diffusions with time varying drift and diffusion coefficient. Several approaches to modelling the diffusion coefficient are described. To perform model selection, we propose an approximation to the Bayes factor that uses only the discrete…

加性风险模型的半参数分析AI 解读

In contrast to the proportional hazards model, the additive risk model specifies that the hazard function associated with a set of possibly time-varying covariates is the sum of, rather than the product of, the baseline hazard function and the regression function of covariates. This formulation describes a different aspect of the association between covariates and the failure time than the proportional hazards model, and is more plausible than the latter for many…

奇异 Wishart 分布与奇异多元 Beta 分布AI 解读

This paper extends the study of Wishart and multivariate beta distributions to the singular case, where the rank is below the dimensionality. The usual conjugacy is extended to this case. A volume element on the space of positive semidefinite $m \times m$ matrices of rank $n < m$ is introduced and some transformation properties established. The density function is found for all rank-$n$ Wishart distributions as well as the rank-1 multivariate beta distribution. To do that,…

基于扩散过程离散观测的贝叶斯因子AI 解读

We present an approach to model selection for a time series of data on a fine time scale. The underlying process generating the data is modelled as a continuous time stochastic process. The underlying continuous processes are assumed to be diffusions with time varying drift and diffusion coefficient. Several approaches to modelling the diffusion coefficient are described. To perform model selection, we propose an approximation to the Bayes factor that uses only the discrete…

扫描统计量检测伯努利序列变化区段的功效AI 解读

Fu & Curnow (1990) derive recursive equations to find the level of significance and power of a likelihood ratio test for a changed segment of specified length, based on the scan statistic, the maximum number of successes within the specified length. Their method is computationally feasible for segment lengths of 20 or less. We present and evaluate highly accurate approximations as well as bounds for the power function of this test that are computationally feasible even for…