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均值与方差发生马尔可夫状态切换的自回归时间序列：Gibbs 抽样贝叶斯推断AI 解读

The authors examine autoregressive time series models subject to regime switching. A Bayesian framework is develope d in which the unobserved.states, one for each time point, are treated as missing data and then analyzed using the Gibbs sampler. This approac h is straightforward because the conditional posterior distribution of the parameters given the states, and the conditional posterior distribution of the states given the parameters, are amenable to simulation. The…

汇率的长记忆AI 解读

Using the Geweke-Porter-Hudak test, the author finds evidence of long memory in exchange-rate data. This implies t hat the empirical evidence of unit roots in exchange rates may not be robust to long-memory alternatives. Fractionally integrated autoregressive moving average models are estimated by both the time-domain exact maximum likelihood method and the frequency-domain approximate maximum likelihood method. Impulse-response functions and forecasts based.on these…

时间序列水平突变的检测AI 解读

This article demonstrates the difficulty that traditional outlier detection methods, such as that of R. S. Tsay, have in identifying level shifts in time series. Initializing the outlier/level-shift search with an estimated autoregressive moving average model lowers the power of the level-shift detection statisti cs. Furthermore, the rule employed by these methods for distinguishing between level shifts and innovation outliers does not work well in t he presence of level…

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非平稳自回归中的 OLS 偏差AI 解读

An analytical formula is derived to approximate the finite sample bias of the ordinary least-squares (OLS) estimator of the autoregressive parameter when the underlying process has a unit root. It is found that the bias is expressible in terms of parabolic cylinder functions which are easy to compute. Numerical evaluation of the formula reveals that the approximation is very accurate. The derived formula inspires a heuristic approximation, obtained by leastsquares fitting of…

含滞后因变量回归的不同偏差近似AI 解读

The small sample bias of the least-squares coefficient estimator is examined in the dynamic multiple linear regression model with normally distributed whitenoise disturbances and an arbitrary number of regressors which are all exogenous except for the one-period lagged-dependent variable. We employ large sample ( T → ∞) and small disturbance (σ → 0) asymptotic theory and derive and compare expressions to O ( T −1 ) and to O (σ 2 ), respectively, for the bias in the…

伪回归、协整与近协整渐近理论的另一种研究方法AI 解读

An alternative approach is taken to the asymptotic theory of cointegration. The present approach gives a different expression for the limiting distributions of statistics associated with cointegration, which enables us to compute accurately the distribution functions. Alternative interpretations of cointegration are given and a notion of near cointegration is introduced. We then devise tests which take cointegration as the null and discuss the limiting local power under the…

带线性约束的协整向量估计AI 解读

A general approach for the estimation of cointegration vectors with linear restrictions is described. In the special case of zero restrictions, the cointegration relations of the paper are formally similar to the structural form of a traditional simultaneous equation model. The proposed estimation procedures require a conventional rank condition of identification but no exogeneity assumption. In place of exogenous variables there are series that are not cointegrated and can…

联立方程误差成分模型估计及其在发展中国家对外贸易中的应用AI 解读

Abstract An empirical balance of payments model involving the demand and supply of imports and exports for 31 developing countries is estimated utilizing panel data over 1964‐1987. In order to compute error‐components 3SLS estimates of this model, which requires different instruments for different equations, we propose a generalization of the Fuller‐Battese transformation to obtain GMM estimates. Our empirical results suggest that very little of the short‐run adjustment in…

二阶自回归多项式根的大样本分布AI 解读

The roots of the characteristic polynomial of an autoregressive process are sometimes of interest. In this paper, we show that the estimated roots of a second order autoregressive polynomial have different asymptotic distributions depending upon whether the true roots are equal or unequal.

含确定性趋势的自回归积分移动平均模型中的若干单位根检验AI 解读

For a nonstationary time series we consider a model which can accommodate the possibility of deterministic and stochastic trends. Assuming that we are primarily interested in testing for the stochastic trend, that is, for a unit root in the time series, we employ the Lagrange multiplier principle and obtain test statistics. The asymptotic distributions of the test statistics. The asymptotic distributions of the test statistics are characterized by functionals of stochastic…

通过广义线性回归拟合长记忆模型AI 解读

There is an increasing awareness of the importance of long-memory models in statistical applications. If long memory is present, it has to be taken into account in order to obtain reliable tests and confidence intervals. One obstacle to using models with long memory in routine statistical analysis has been the lack of easily available and sufficiently versatile statistical software. Here we propose a simple but flexible class of parametric models, which can be used to model…

分数差分 ARIMA 过程的可逆性AI 解读

To evaluate how the condition for invertibility of fractional ARIMA (p, d, q) processes can be achieved, we formulate a measure based on the prediction error related to the autoregressive inversion. Some results are obtained by investigating the behaviour of the measure. A conclusion is that the condition for invertibility is satisfied when the degree of fractionally differencing d exceeds −1. As another one, it is pointed out that invertibility is not so easily achieved…

分数噪声样本自相关的偏差AI 解读

The autocorrelation function of fractional noise, when the difference parameter is positive, is quite distinctive. However, for time series of moderate length, this pattern is unlikely to be seen in the sample autocorrelations, which are severely biased when the process mean is unknown.

类别时间序列的谱分析：数值赋值与谱包络AI 解读

Many studies produce categorical time series in which harmonic analysis is of interest. Although there exist time domain approaches for the analysis of categorical time series such as Markov chains or link function based regression models, there is apparently little statistical theory or methodology for analyzing qualitative-valued time series in the frequency domain. The purpose of this paper is to initiate the development of a general framework for the frequency domain…

破纪录数据问题的参数似然推断AI 解读

In this paper we consider the analysis of record breaking data sets, where only observations that exceed, or only those that fall below, the current extreme value are recorded. Example application areas include industrial stress testing, meteorological analysis, sporting and athletic events, and oil and mining surveys. A closely related area is that of threshold modelling, where the observations are those that cross a certain threshold value. The inherent missing data…

多步预测中最大似然估计的稳健性：指数平滑情形AI 解读

We extend the argument initiated by Cox (1961) that the exponential smoothing formula can be made more robust for multi-step forecasts if the smoothing parameter is adjusted as a function of the forecast horizon l. The consistency property of the estimator which minimizes the sum of squares of the sample l-step ahead forecast errors makes the robustness result useful in practice. We also generalize the consistency result to some other parsimonious nonstationary models which…

基于经验分布函数的序列独立性非参数检验AI 解读

The Blum, Kiefer & Rosenblatt (1961) statistic for testing independence is considered in a time series setting. This test is, under mild conditions, shown to be consistent against lag one dependent alternatives. The null distribution of the test statistic is established, both when the marginal distribution is continuous and when it is discrete. Simulation results giving information on the size and the power of the test are provided, and comparisons are made with other tests…

含脉冲连续过程采样时间序列的状态空间建模AI 解读

A non-Gaussian time series model useful for describing the dynamics of endocrinological data is introduced by using a state-space representation. This model is applicable even when the data are sparsely sampled in comparison with time lengths of pulses. Likelihood-based methods of inference for the model are developed. By fitting the present model to partially observed hormonal time series data, we can estimate the locations and heights of the peaks of the pulses as well as…

状态空间模型的扰动平滑器AI 解读

This paper develops a method to evaluate the smoothed estimator of the disturbance vector in a state space model together with its mean squared error matrix. This disturbance smoother also leads to an efficient smoother for the state vector. Applications include a method to calculate auxiliary residuals for unobserved components time series models and an EM algorithm for estimating covariance parameters in a state space model.

流行型备择下的变点检验AI 解读

The purpose of this paper is to discuss the tests to detect an epidemic alternative in the mean value of a sequence of independent normal variables. Various test statistics, such as the likelihood ratio, the score-like statistic, Levin & Kline's statistic, the semilikelihood ratio, and the recursive residual, are studied. The large deviation approximations to the significance levels and powers are developed by integrating approximations to conditional boundary crossing…

α 混合随机变量三角阵列的一般重抽样方案及谱密度估计应用AI 解读

In 1989 Kunsch introduced a modified bootstrap and jackknife for a statistic which is used to estimate a parameter of the $m$-dimensional joint distribution of stationary and $\alpha$-mixing observations. The modification amounts to resampling whole blocks of consecutive observations, or deleting whole blocks one at a time. Liu and Singh independently proposed (in 1988) the same technique for observations that are $m$-dependent. However, many time-series statistics, notably…

贝叶斯网络中的参数更新AI 解读

A Bayes network is a directed acyclic graph in which the links are quantified by fixed conditional probabilities and the nodes represent random variables. The primary use of the network is to provide an efficient method for updating conditional probabilities in the graph. We consider the consequences of using the network as the computational device for updating parameter estimates in the dynamic linear model, a discrete time Bayesian model. We show that using the network…

线性平滑器的频域诊断AI 解读

Frequency domain analysis is used to examine estimates from linear smoothers operating on realizations of random fields over space and/or time. The estimates are expressed in terms of the Fourier transforms of the dependent variable and of the smoother weights. The latter is referred to as the equivalent transfer function. The data do not need to be evenly spaced to perform this analysis. The modulus of the equivalent transfer function characterizes the spectral content of…