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序列相关与预测组合AI 解读

It is shown that regression-based methods of forecast combination lead to serially correlated combined prediction errors. The form of the serial correlation is characterized, and specification, estimation, and prediction are treated. A fully optimal combined predictor, which exploits the serial correlation, is developed and compared with existing regression-based methods in a numerical example, leading to decreases in mean squared prediction error.

统计过程控制中的时间序列建模AI 解读

In statistical process control, a state of statistical control is identified with a process generating independent and identically distributed random variables. It is often difficult in practice to attain a state of statistical control in this strict sense; autocorrelations and other systematic time-series effects are often substantial. In the face of these effects, standard control-chart procedures can be seriously misleading. We propose and illustrate statistical modeling…

This article attempts to establish the nature of the relationship between monetary assets by estimating a sequence of four nested demand systems: the generalized translog, the basic translog, the linear translog, and the homothetic translog. The principal attraction of the empirical work is that I am able to test separately for both homothetic and quasi-homothetic preferences over monetary assets. The tests reject both homotheticity and quasi-homotheticity and thus…

By replacing the unknown random factors of factor analysis with observed macroeconomic variables, the arbitrage pricing theory (APT) is recast as a multivariate nonlinear regression model with across-equation restrictions. An explicit theoretical justification for the inclusion of an arbitrary, well-diversified market index is given. Using monthly returns on 70 stocks, iterated nonlinear seemingly unrelated regression techniques are employed to obtain joint estimates of…

平稳一阶自回归模型中的Student t近似AI 解读

The exact distribution of the regression t statistic for testing the value of the AR parameter in a Gaussian first ord er autoregressive model is investigated by Monte Carlo methods. The S tudent's t distribution is not a satisfactory approximation for sampl es typical in economic applications. The main problem is the location of the distribution of the t statistic rather than the shape. Once t he t statistic is adjusted so that it has the same mean and standard deviation as…

对《时间序列回归中分离需求与供给的一种被忽视方法》评论的回复AI 解读

Stephen E. Haynes, Joe A. Stone, [Comment on "A Neglected Method of Separating Demand and Supply in Time Series Regression," by Stephen E. Haynes and Joe A. Stone]: Reply, Journal of Business & Economic Statistics, Vol. 6, No. 1 (Jan., 1988), pp. 138-140

关于《时间序列回归中分离需求与供给的一种被忽视的方法》的评论AI 解读

Kan H. Young, Comment on "A Neglected Method of Separating Demand and Supply in Time Series Regression," by Stephen E. Haynes and Joe A. Stone, Journal of Business & Economic Statistics, Vol. 6, No. 1 (Jan., 1988), pp. 135-138

英国凯恩斯主义宏观计量模型：1955—1984 年AI 解读

Abstract In this paper we present a small Keynesian macro‐economic model in which wage‐price determination is linked to the working of goods and money markets. By explicitly treating the Keynes effect we derive a general expression for the employment‐money supply elasticity, and draw the IS‐LM loci in the employment‐interest rate space Our empirical specification allows for short‐run disequilibrium dynamic adjustments around the static long‐run relations predicted by the…

非高斯时间序列的相位滞后估计AI 解读

An important problem in the physical sciences is estimation of the innovations of a noninvertible linear process. Here the problem of deconvolving such a time series containing a phase-lead is investigated. A compensating phase-lag filter is sought, and is estimated by maximization of a chosen statistic or projection index. It is demonstrated by simulation that a statistic which is superior to another in the ideal case of a full-band time series can be substantially inferior…

带有偏置扰动的多过程动态线性模型：生长激素水平的实时建模AI 解读

This paper introduces biased perturbation distributions into the multiprocess dynamic linear model in order to represent growth hormone levels in animals, which are characteristically noisy pulsatile time series. The use of biased perturbation distributions allows a pulse to be detected on the first observation immediately after it occurs, thus allowing the process to be modelled in real time. This approach is found to be quite effective at detecting the occurrence of a…

计数时间序列的回归模型AI 解读

This paper discusses a model for regression analysis with a time series of counts. Correlation is assumed to arise from an unobservable process added to the linear predictor in a log linear model. An estimating equation approach used for parameter estimation leads to an iterative weighted and filtered least-squares algorithm. Asymptotic properties for the regression coefficients are presented. We illustrate the technique with an analysis of trends in U.S. polio incidence…

状态空间模型中平滑估计的协方差AI 解读

Ansley & Kohn (1982) presented a novel proof of the fixed interval smoothing algorithm for state space models. In this note the ideas of their proof are used to provide a new formula for the covariance between smoothed estimates at any two points in time. This equation is substantially simpler than existing special cases.

时间序列模型的交叉验证滤波器AI 解读

A filter is presented which computes cross-validation errors and associated statistics for an arbitrary state space model. The procedure is more efficient than an existing approach. Diffuse initial conditions are easily handled using a minor extension. The relationship to the fixed interval smoothing algorithm is investigated.

结构化参数多元自回归模型中残差自协方差的分布AI 解读

The asymptotic distribution is derived for residual autocovariances in the multivariate autoregressive model with structured parameterization, a form often employed in multivariate time series modelling to achieve parsimony. It is shown that a similar result for the asymptotic distribution of a portmanteau statistic for the usual full-rank autoregressive-moving average model can be extended to the autoregressive model with structured parameterization.

时间序列数据窗的均方误差准则AI 解读

A periodogram mean integrated squared error criterion is proposed for assessing the performance of time series data windows, or tapers. The criterion is evaluated numerically for several known autoregressive processes to determine the optimal amount of tapering in Tukey's cosine window. It is found that tapering can be extremely beneficial if the spectrum contains sharp peaks. Also, in all cases studied, the optimal number of points tapered converges to a constant as the…

阶数估计对自回归谱密度峰值频率估计的影响AI 解读

The effect of estimating the order of an autoregressive process on estimating the peak frequency is examined. For consistent order determining methods it is shown that the asymptotic results are the same as for the case when the order is known. For the order criteria which asymptotically overestimate the order, the peak frequency estimator is shown to be a consistent estimator of the true peak frequency.

论频率估计AI 解读

This paper discusses a least-squares procedure and the use of the periodogram for isolating a discrete harmonic of a time series. It is shown that the usual asymptotics on estimation of frequency, amplitude and phase of such a harmonic have to be used with great caution from a moderate sample perspective. Computational issues are discussed and some illustrations are provided. Bolt & Brillinger (1979) make use of these asymptotic results.

重抽样方法中的鞍点近似AI 解读

Saddlepoint approximations are shown to be easy to use and accurate in a variety of simple bootstrap and randomization applications. Examples include mean estimation, ratio estimation, two-sample comparisons, and autoregressive estimation.

二阶 Fisher 信息AI 解读

The paper presents general second-order approximate formulae for the Fisher information of asymptotically normal statistics, and applies the formulae to a stationary time-series model as well as to an econometric simultaneous equation model. Also the second-order conditional information is evaluated for the exponential family and the location family. Conditioned on a second-order ancillary statistic, the second-order information loss of the maximum likelihood estimate is…

稳健时间序列建模中的拟合优度检验AI 解读

The problem of testing the adequacy of a time series model in the presence of outliers is considered. The classical portmanteau statistic is generalized to an important class of robust estimators. Some Monte Carlo results suggest that the proposed generalization possesses good robustness properties over the classical statistic. A robustified version of a result of Newbold (1980) is also obtained.

时间序列回归中的单位根检验AI 解读

This paper proposes new tests for detecting the presence of a unit root in quite general time series models. Our approach is nonparametric with respect to nuisance parameters and thereby allows for a very wide class of weakly dependent and possibly heterogeneously distributed data. The tests accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend. The…

状态空间模型的似然AI 解读

This paper derives an expression for the likelihood for a state space model. The expression can be evaluated with the Kalman filter initialized at a starting state estimate of zero and associated estimation error covariance matrix of zero. Adjustment for initial conditions can be made after filtering. Accordingly, initial conditions can be modelled without filtering implications. In particular initial conditions can be modelled as ‘diffuse’. The connection between the…

大量小样本中的序列相关检验AI 解读

Methods are outlined for testing for serial correlation in large numbers of small samples, emphasis being placed on samples of size three. Some data on pulse rates are analysed in illustration.

非高斯平稳时间序列的时间可逆性与移动平均表示唯一性AI 解读

A recent result by Findley (1986) on the uniqueness of moving average representations for non-Gaussian time series is shown to establish a conjecture by Weiss (1975) on the time-reversibility of general linear processes.