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时间序列分析中的“无限方差”与研究策略AI 解读

The possibility that some time series that arise in economics have error or innovation terms that come from infinite variance distributions throws doubt on most of the classical methods of analysis. The evidence in favor of infinite-variance is discussed and a variety of alternative explanations of the long-tailed property of observed distributions examined. Some of these alternative explanations are based on mixtures of distributions and suggest data-transformations that…

宽平稳自回归序列观测均值的估计AI 解读

This study concerns the relative efficiency of the least-squares estimator of the mean of a covariance stationary sequence that has a constant mean and an autoregressive representation of order p. Our results augment those in [2]. The results in Section 1 include for any positive integer p the variance of the LSE, the BLUE in terms of autoregressive coefficients, the variance of the BLUE and the range of applications of Ylvisaker's theorem [7] regarding a lower bound on…

分布滞后模型中的季节变动AI 解读

The dependent variable in a distributed lag model frequently exhibits a distinct seasonal pattern which cannot be attributed to the seasonal behavior of the independent variable. This article illustrates the advantages of using the variable lag model to incorporate these seasonal influences directly into the distributed lag relationship.

简单马尔可夫链自相关系数的估计AI 解读

Four estimates of the autocorrelation in simple Markov chains are given and their asymptotic normality established. Exact moment generating functions of two of the estimates are obtained. These estimates are compared with the maximum likelihood estimate.

非循环序列相关系数的近似分布AI 解读

The paper applies a smoothing technique to obtain an approximate sampling distribution of a noncircular serial correlation coefficient. This technique is similar to the one employed by Koopmans and Dixon for finding the circular counterpart and thus provides an immediate comparison with that of the circularly denned coefficient. In fact, it is shown that the latter is a special case of the present result which is obtained in a generalized Leipnik's form with a correction…

动态扰动时间序列模型的最小二乘估计AI 解读

Recent results of the author concerning large-sample properties of the nonlinear least squares estimates of the parameters, in a regression model in which the disturbances follow a stationary mixed autoregressive-moving average time series, are extended to models in which lagged values of the dependent and independent variables occur.

动态扰动时间序列模型中的最小二乘估计AI 解读

Recent results of the author concerning large-sample properties of the nonlinear least squares estimates of the parameters, in a regression model in which the disturbances follow a stationary mixed autoregressive-moving average time series, are extended to models in which lagged values of the dependent and independent variables occur.

非循环序列相关系数的近似分布AI 解读

The paper applies a smoothing technique to obtain an approximate sampling distribution of a noncircular serial correlation coefficient. This technique is similar to the one employed by Koopmans and Dixon for finding the circular counterpart and thus provides an immediate comparison with that of the circularly denned coefficient. In fact, it is shown that the latter is a special case of the present result which is obtained in a generalized Leipnik's form with a correction…

分布滞后模型中参数的近似分布AI 解读

In the construction of econometric models, the need frequently arises to test the significance of coefficients whose distribution is a ratio of two normal random variables for which no statistical tables exist. In this article the distribution of such a ratio, emanating from a partial adjustment model, is empirically approximated by utilizing Monte Carlo experiments with various sample sizes. The results indicate that the standardized distribution of the ratio is positively…

利用一般线性统计模型对经济数据进行季节调整AI 解读

This article presents a technique of seasonal adjustment of economic time series within the framework of the general linear statistical model. The technique is designed to be flexible enough to be applicable to varying types of economic time series. The first goal of the technique is the development of a specification that allows adequate flexibility in the estimation of the trend-cycle component of a time series. The second goal is the development of a method of handling…

用一般线性统计模型对经济数据进行季节调整AI 解读

This article presents a technique of seasonal adjustment of economic time series within the framework of the general linear statistical model. The technique is designed to be flexible enough to be applicable to varying types of economic time series. The first goal of the technique is the development of a specification that allows adequate flexibility in the estimation of the trend-cycle component of a time series. The second goal is the development of a method of handling…

对《国防订单库存影响估计的一致性评论》的回应AI 解读

Gramlich and Galper (hereafter referred to as GG) indeed have performed a useful service by pointing out that an erroneous equation was included in my paper [3]. The corrected inventory change equation, the equation with all lagged orders included, was almost identical with the results obtained by applying GG's method (ii) to the order-inventory stock equation presented in Column (2), Table IV of my paper [3, p. 161]. The results are consistent when GG's methods (ii) and…

线性开环系统时变性的检验AI 解读

Summary We consider the problem of testing a given open-loop system for time-dependence. The test is based on just a single realization of the input and a single realization of the output. It makes use of the concept of the “evolutionary cross-spectra” of a non-stationary vector process and rests essentially on testing the “uniformity” of a set of vectors, whose components consist of the “evolutionary gain-spectra” and “evolutionary phase-spectra”. Using a logarithmic…

时间序列预测误差研究AI 解读

Parametric and nonparametric procedures for the prediction of a time series are discussed. In each case the increase in the mean squared error of prediction, over its minimum level, due to the use of estimated spectra is assessed. The fitting of simple parametric models as approximations is also discussed.

时间序列时间聚合的渐近行为AI 解读

The problem of modelling and forecasting temporal aggregates of time series is discussed. Let zt be the basic series and xT be the m-component temporal aggregatos. Forecasts of future xT may be constructed from data on (i) zt or (ii) xT. It is shown that, for large m, there is no gain in using the basic data if zt is stationary, but considerable gain can be obtained when zt is nonstationary.

一阶自回归序列参数的最大似然估计量分布AI 解读

A method is given for obtaining values of the distribution function of the maximum likelihood estimator of the parameter in the first-order autoregressive series. Although exact results are obtainable in a special case, in general the distribution function involves the approximation of the distribution of a linear combination of chi-squared variates. Two such approximations are compared with simulated results. The method used is valid for any value of the parameter.

构造经济预测经验置信限的简便方法AI 解读

A simple method for the construction of empirical confidence intervals for time series forecasts is described. The procedure is to go through the series making a forecast from each point in time. The comparison of these forecasts with the known actual observations will yield an empirical distribution of forecasting errors. This distribution can then be used to set confidence intervals for subsequent forecasts. The technique appears to be particularly useful when the…

相干性与群时延的估计AI 解读

The usual estimation of coherence is known to be badly biased towards zero if over the band of frequencies used for its estimation the phase is changing rapidly, as in the case of large group delay. The usual asymptotic distribution theory for spectral estimates is of no value in this circumstance, since it does not involve the group delay. A new theory is used to obtain estimates of coherence and group delay, which is itself of considerable physical interest, and the…

弱平稳点过程与随机测度AI 解读

Summary A weakly stationary point process on the real line is a point process with counting measure N(A) defined on Borel subsets A of the real line such that the first two moments of N(A) are finite for bounded Borel sets and invariant under translation. The expected number of points falling in an interval of length u equals μu and serves to define the intensity parameter μ of the process. The variance of the number of points falling in an interval of length u defines the…

含移动平均误差的多方程系统的识别问题AI 解读

where y(t) and x(t) are vectors of G components, z(t) has K components, B is a G x G matrix, and F is a G x K matrix.' The components of z(t) are predetermined at time t and the vector x(t) is not serially correlated, so that (among other requirements) we have

具有自回归移动平均误差的回归模型的最小二乘估计AI 解读

To treat the problem of correlated errors in regression, a model in which the errors follow a stationary autoregressive-moving average time series is suggested. Simultaneous least squares estimation of the regression and the time series parameters is discussed, and it is shown that asymptotically the estimates obtained in this manner possess normal distributions, whether or not the errors themselves are normally distributed. The estimates of the regression parameters are…

一类受噪声污染的平稳与非平稳信号的近似最优线性预测AI 解读

A technique for approximating the best linear predictor of a noise-distorted signal is presented. The technique is applicable when the signal is stationary with a spectrum which is highly concentrated around known or estimated frequencies, or when the signal is an accumulating sequence whose “spectrum” has poles at these frequencies. The noise must be stationary, but its spectrum need only be known or estimated at the above-mentioned frequencies. The time parameter is…

最小二乘估计稳定季节模式的效率AI 解读

In this article we investigate the efficiency of least squares (l.s.) in estimating a stable pattern. A model is proposed for an economic time series, which, after filtering, is a suitable basis for our investigation. The covariance structure of the disturbances is assumed known and several possible generating processes for the disturbances are considered. We contrast the variances of the l.s. estimates with those from the best linear unbiased (b.l.u.) procedure for four…

一类平稳与非平稳含噪信号的近似最优线性预测AI 解读

A technique for approximating the best linear predictor of a noise-distorted signal is presented. The technique is applicable when the signal is stationary with a spectrum which is highly concentrated around known or estimated frequencies, or when the signal is an accumulating sequence whose “spectrum” has poles at these frequencies. The noise must be stationary, but its spectrum need only be known or estimated at the above-mentioned frequencies. The time parameter is…