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预测组合的混合模型方法AI 解读

A multiprocess mixture-model approach to combining forecasts from alternative sources is proposed. This approach extends the Granger-Ramanathan method by allowing the weights used in producing the combination forecast to vary over time. In addition, the procedure discounts outlying data points that arise during time periods when all of the competing forecasts miss the mark. An empirical comparison with traditional and more recently proposed.combination methods demonstrates…

总量冲击与宏观经济波动：贝叶斯方法AI 解读

Abstract This paper describes Bayesian techniques for analysing the effects of aggregate shocks on macroeconomic time‐series. Rather than calculate point estimates of the response of a time‐series to an aggregate shock, we calculate the whole probability density function of the response and use Monte‐Carlo or Gibbs sampling techniques to evaluate its properties. The proposed techniques impose identification restrictions in a way that includes the uncertainty in these…

基于最小消息长度估计的单因子分析AI 解读

SUMMARY The minimum message length (MML) technique is applied to the problem of estimating the parameters of a multivariate Gaussian model in which the correlation structure is modelled by a single common factor. Implicit estimator equations are derived and compared with those obtained from a maximum likelihood (ML) analysis. Unlike ML, the MML estimators remain consistent when used to estimate both the factor loadings and the factor scores. Tests on simulated data show the…

跟踪软件可靠性增长的非齐次自回归过程及贝叶斯分析AI 解读

SUMMARY We motivate a non-homogeneous autoregressive process as a model for reliability growth and consider two formulations, both Bayesian, which alleviate a limitation that least squares estimators for such processes of order greater than 1 exist only when repeated measurements of the time series are available. In one formulation, the prior assumption involves exchangeability of coefficients, whereas in the other an autoregressive structure is imposed on them. Both…

带非参数回归趋势的自回归过程均值平稳性检验AI 解读

In this paper, we suggest tests of stationarity in the mean of autoregressive time series versus arbitrary trend alternatives. As an intermediate, though essential, step local asymptotic normality of autoregressive models with a nonparametric regression trend is established. Moreover, a functional central limit theorem for the underlying likelihood ratio processes is derived. These results then offer a general construction principle by which every goodness of fit test (case…

泊松过程变化点的对数线性模型AI 解读

Many methods have been proposed for modelling nonhomogeneous Poisson processes, including change point models and log-linear models. In this paper, we use likelihood ratio tests to choose which of these models are necessary. Of particular interest is the test for the presence of a change point, for which standard asymptotic theory is not valid. Large deviation methods are applied to approximate the significance level, and power approximations are given. Confidence regions…

谱密度峰值位置的弱收敛与自适应估计AI 解读

Adaptive nonparametric kernel estimators for the location of a peak of the spectral density of a stationary time series are proposed and investigated. They are based on direct smoothing of the periodogram where the amount of smoothing is determined automatically in an asymptotically optimal fashion. These adaptive estimators minimize the asymptotic mean squared error. Adaptivity is derived from the weak convergence of a two-parameter stochastic process in a deviation and a…

估计矩阵的秩与定性检验：因子、状态空间及 ARMA 应用AI 解读

Consider any consistent, asymptotically normal estimate ǎ of an arbitrary rectangular or square matrix A. This article derives an explicit test for the rank of A and a related test of (semi) definiteness of A. Potential applications include testing for identification of structural models, testing for the number of state variables in state-space models (including tests for the order of autoregressive moving average (ARMA) processes), consumer demand analysis applications, and…

多元动态线性变量误差模型的可识别性AI 解读

This article considers multivariate causal transfer function systems with latent stationary inputs and outputs. Their observation is assumed to be disturbed by errors in variables (EV). The main identification results for such models so far consist of structure theory. Derived are descriptions of classes of EV transfer function systems compatible with given covariance structures of the observed variables under various causality constraints. The case of unique determination…

用非参数回归估计混沌系统的李雅普诺夫指数AI 解读

We discuss procedures based on nonparametric regression for estimating the dominant Lyapunov Exponent λ1 from time series data generated by a nonlinear autoregressive system with additive noise. For systems with bounded fluctuations, λ1 > 0 is the defining feature of chaos. Thus our procedures can be used to examine time series data for evidence of chaotic dynamics. We show that a consistent estimator of the partial derivatives of the autoregression function can be used to…

利用条件密度混合估计层级模型边际后验密度AI 解读

A technique called quantile integration is proposed for the estimation of marginal posterior densities arising in Bayesian models having hierarchical representations. The method is based on approximating marginal densities as mixtures of conditional densities, where the conditioning variables are selected deterministically from the mixing distributions. The form of the approximation makes it easy to implement, and the resulting approximations are computationally efficient to…

重复测量实验中允许时间异方差的 ARMA 协方差结构AI 解读

Rochon and Helms (1989) presented a model for analyzing repeated measures experiments. The general linear model was used to assess the influence of covariate information, and ARMA time series models were put forward to characterize the covariance matrix among the repeated measures. Practical experience has suggested, however, that the ARMA assumption of constant variances and autocovariances over time is too restrictive for many applications. For example, observations may be…

利用条件密度混合估计层级模型边际后验密度的方法AI 解读

A technique called quantile integration is proposed for the estimation of marginal posterior densities arising in Bayesian models having hierarchical representations. The method is based on approximating marginal densities as mixtures of conditional densities, where the conditioning variables are selected deterministically from the mixing distributions. The form of the approximation makes it easy to implement, and the resulting approximations are computationally efficient to…

多变量动态线性变量测量误差模型的可识别性AI 解读

This article considers multivariate causal transfer function systems with latent stationary inputs and outputs. Their observation is assumed to be disturbed by errors in variables (EV). The main identification results for such models so far consist of structure theory. Derived are descriptions of classes of EV transfer function systems compatible with given covariance structures of the observed variables under various causality constraints. The case of unique determination…

序列相关的方差比检验何时最优？AI 解读

This paper considers a class of statistics that can be written as the ratio of the sample variance of a filtered time series to the sample variance of the original series. Any such statistic is shown to be optimal under normality for testing a null of white noise against some class of serially dependent alternatives. A simple characterization of the alternative class is provided. The results are used to show that a variance ratio test for mean reversion is an optimal test…

经济学中一类线性过程模型的经验分布渐近性质AI 解读

Let … be a moving average process of infinite order where the innovations ε( k ) are in the domain of attraction of a stable law with index α ε (0, 2) and the parameter sequence decreases at a polynomial or exponential rate. These and similar processes have recently received increased attention both in the econometrics and statistics/probability literature. The present paper studies almost sure uniform rates of convergence of the empirical distribution function. Applications…

长程相依时间序列的拟合优度检验AI 解读

SUMMARY We propose a test statistic for goodness of fit in time series with slowly decaying serial correlations. The asymptotic distribution of the test statistic, originally proposed by Milhoj for time series with smooth spectra, turns out to be the same, under the null hypothesis, even if the spectrum has a pole at 0. In particular, the test is suitable to detect lack of independence in the observations, or estimated residuals, if the first few correlations are small but…

对数线性模型的加总AI 解读

When economic theory suggests a log-linear specification for individual agents, e.g., Cobb-Douglas production, it is common to estimate the same log-linear model with aggregate data, invoking a representative agent assumption and thereby assuming away aggregation errors. This paper gives necessary and sufficient restrictions on the distribution of agents in an economy for log-linear agent models to aggregate into log-linear macro models, and discusses the aggregation bias…

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带端点约束的多项式分布滞后与超前项估计AI 解读

This paper considers the use of the polynomial distributed lag (PDL) technique when the lag length is estimated rather than fixed. We focus on the case where the degree of the polynomial is fixed, the polynomial is constrained to be zero at a certain lag length q, and q is estimated along with the other parameters. We extend the traditional PDL setup by allowing q to be real-valued rather than integer-valued, and we derive the asymptotic covariance matrix of all the…

存在确定性趋势时协整向量的有效估计与检验AI 解读

Estimation and inference in cointegrated models is examined in the presence of deterministic trends in the data. It is suggested that trends be excluded in the levels regression for maximal efficiency. Fully modified test statistics are asymptotically chi-square. A chi-square test for the validity of trend exclusion is presented. The asymptotic distributions of standard cointegration test statistics are shown to depend both upon regressor trends and estimation detrending…

评估利率期限结构的预期假说：协整向量分析AI 解读

The author tests cointegration restrictions that are consistent with the expectations hypothesis of the term structure by employing the full-information maximum likelihood methods developed by S. Johansen. Yield curves appear to be the result of cointegration among interest rates. The cointegration vectors that best describe the long-term impact of interest-rate levels on interest-rate changes can often be written as linear combinations of interest-rate spreads. There is,…

非平稳性与水平突变：购买力平价应用AI 解读

The authors consider testing for a unit root in a time series with a structural change in mean occurring at an unknown date. They derive and tabulate the asymptotic distributions of the minimal t-statistic over all possible break points (and other related statistics) in the appropriate regressions. However, emphasis is given to the tabulation of finite sample critical values with particular attention given to the effect of various procedures to select the order of the…