日期精度：到日 1895 篇 · 到月 4221 篇 · 到年 383 篇 · 未提供 5 篇
分数差分时间序列建模
Aspects of model building using fractionally differenced autoregressive-moving average processes are discussed. An algorithm for approximate maximum likelihood estimation is outlined and the large-sample distribution of the maximum likelihood estimates is derived. The large-sample distribution of the residual autocorrelations is also derived and a modified portmanteau test statistic is obtained for checking model adequacy.
高阶交叉的渐近方差及其快速白噪声检验应用
The rate of decrease in the variance of higher order crossings is obtained for stationary m-dependent Gaussian sequences. This result provides a quick approximation to the variance of the number of axis-crossings of m-dependent processes, and is applied in determining approximate probability limits for the higher order crossings of white noise. The limits are used in testing for white noise in simulated and also real data examples.
Bootstrap 在功率谱密度估计中的应用
A shortcoming in the use of autoregressive spectral estimation has been the lack of methods for placing confidence intervals or bands on estimated spectral density. The bootstrap method is applied to obtain nonparametric confidence bands and intervals. It is the aim of this paper to indicate how this can be done and to report on the outcome of some Monte Carlo studies of the properties of the resulting procedures. Some asymptotic theory concerning the properties of the…
初始条件未完全指定的状态空间模型：估计、滤波与平滑
The likelihood is defined for a state space model with incompletely specified initial conditions by transforming the data to eliminate the dependence on the unspecified conditions. This approach is extended to obtain estimates of the state vectors and predictors and interpolators for missing observations. It is then shown that this method is equivalent to placing a diffuse prior distribution on the unspecified part of the initial state vector, and modified versions of the…
误设自回归时间序列模型中预测量的性质
This article investigates major effects of misspecification in stationary linear time series models when we fit a pth-order autoregressive model. The true model can be an autoregressive moving average model. We derive the formulas of bias and mean squared error (MSE) of the least squares estimator and the hth period ahead prediction MSE in the time domain. Contrary to previous studies, the process in estimation is not necessarily independent of the process in prediction, and…
谱估计的数据驱动选择：拓展交叉验证方法的适用范围
I develop methods of objectively choosing a spectrum estimate from a general class C of available estimates. C can, for example, simultaneously include Blackman—Tukey and autoregressive estimates, so the statistician no longer needs to choose one type or the other arbitrarily. The methods work by extending the applicability of existing cross-validatory techniques through the introduction of generalized leave-out-one spectrum estimates. As special cases, I obtain new…
一阶自相关误差下线性回归估计量的效率比较
This article compares several estimators for linear regression models with first-order autocorrelated errors. Asymptotic variances of the estimators of regression coefficients are obtained up to order T −2 for the maximum likelihood, the iterated Prais-Winsten, and the iterated Cochrane—Orcutt methods. It is shown that the first two methods are equivalent in efficiency and that the last is less efficient. This loss in efficiency is due to the effect of the initial…
谱估计的数据驱动选择：拓展交叉验证方法的适用范围
I develop methods of objectively choosing a spectrum estimate from a general class C of available estimates. C can, for example, simultaneously include Blackman—Tukey and autoregressive estimates, so the statistician no longer needs to choose one type or the other arbitrarily. The methods work by extending the applicability of existing cross-validatory techniques through the introduction of generalized leave-out-one spectrum estimates. As special cases, I obtain new…
时间序列回归模型的高效估计与预测
For a time series regression model with correlated residuals we show how to compute efficiently the likelihood, predict future values and interpolate missing values. As an illustration we consider a regression model with autoregressive moving average residuals.
自回归移动平均过程的 Levinson–Durbin 递推
We discuss an algorithm which allows for recursive-in-order calculation of the parameters of autoregressive-moving average processes. The proposed procedure generalizes the recursion of Levinson (1946) and Durbin (1960), which applies in the pure autoregressive case. We use ideas similar to the multivariate autoregressive case. Our results suggest how estimation procedures for autoregressive-moving average parameters, which include an automatic choice of model order, for…
估计向量自回归模型预测的无偏性
Forecasts from a univariate autoregressive model estimated by OLS are unbiased, irrespective of whether the model fitted has the correct order; this property only requires symmetry of the distribution of the innovations. In this paper, this result is generalized to vector autoregressions and a wide class of multivariate stochastic processes (which include Gaussian stationary multivariate stochastic processes) is described for which unbiasedness of predictions holds:…
非平稳高阶连续时间动态模型的参数估计
This paper is concerned with derivation of a new efficient algorithm for computing the exact Gaussian likelihood for structural parameters in nonstationary higher-order continuous-time dynamic models and with its application in the estimation of these parameters. The algorithm completely avoids the computation of the covariance matrix of the observations and is applicable to a system of any order with mixed stock and flow data. It is used as the basis for an iterative…
线性理性预期模型的解
Linear rational expectations models generally have a large number of solutions. It is thus important to describe them exhaustively in order to study their properties and subsequently estimate which solution best fits the data. In this paper, a global approach is suggested allowing a simultaneous treatment of all possible cases. The fundamental concepts are the revision processes appearing in the procedure of updating expectations. It isfound that the set of solutions is…
序列相关的一般分析框架
In this paper the testing and estimation problems are discussed in the case of serial correlation. Various models are particular cases of the general framework considered: the nonlinear simultaneous equations models, the probit models, the tobit models, the disequilibrium models, the frontier models, etc. In this context, it is shown that the score test can be written explicitly and that the statistic obtained is a generalization of that of Durbin and Watson; moreover, the…
广义矩估计量渐近协方差矩阵下界的计算方法
For many time series estimation problems, there is an infinite-dimensional class of generalized method of moments estimators that are consistent and asymptotically normal. This paper suggests a procedure for calculating the greatest lower bound for the asymptotic covariance matrices of such estimators. The analysis focuses on estimation problems in which the data are generated by a stochastic process that is stationary and ergodic. The calculation of the bound uses…
去趋势对格兰杰因果检验的影响
Nonstationary time series are frequently detrended in empirical investigations by regressing the series on time or a function of time. The effects of the detrending on the tests for causal relationships in the sense of Granger are investigated using quarterly U.S. data. The causal relationships between nominal or real GNP and M1, inferred from the Granger–Sims tests, are shown to depend very much on, among other factors, whether or not series are detrended. Detrending tends…
理性预期与宏观经济预测
The article presents extensive results from testing for bias and serially correlated errors in a collection of time series of quarterly multiperiod forecasts for six variables including real GNP growth, inflation, and unemployment. The analysis covers responses by 79 frequent participants in economic outlook surveys conducted regularly since 1968. It shows much greater incidence of apparently systematic errors for inflation than for the other variables. Also, the tests are…
季节性时间序列与传递函数建模
A simple modification is suggested for the construction of transfer function models relating an output variable Yt to an input variable Xt when the model for Xt contains operators that cancel out. In addition, the evaluation of transfer function models is discussed by comparing the forecasts with the actual observations.
消费者价格指数的无应答评估
A household budget survey often suffers from a high nonresponse rate and a selective response. The bias that may be introduced in the estimation of budget shares because of this nonresponse can affect the estimate of a consumer price index, which is a weighted sum of partial price index numbers (weighted with the estimated budget shares). The bias is especially important when related to the standard error of the estimate. Because of the impossibility of subsampling…
结构时间序列模型与成分的刻画
This article analyzes certain properties of a class of recently proposed structural time series models in which particular structures are imposed upon the unobserved components of an observed time series. It is shown how the overall model can be expected to fit series, such as those for which the X-11 or Airline models are appropriate. As for the components, identification of the model is achieved by assigning a certain amount of white noise variation to the trend and…
针对 ARMA 备择的随机性线性序列秩检验
In this paper we introduce a class of linear serial rank statistics for the problem of testing white noise against alternatives of ARMA serial dependence. The asymptotic normality of the proposed statistics is established, both under the null as well as alternative hypotheses, using LeCam's notion of contiguity. The efficiency properties of the proposed statistics are investigated, and an explicit formulation of the asymptotically most efficient score-generating functions is…
部分观测随机游走中的一致估计
If a discrete-time random walk, consisting of the sum of independent increments from an unknown underlying distribution, is observed at every time instant then it is clear that the underlying distribution can be consistently estimated. If, however, we are restricted to observing only a subset of the times, and if this subset is too sparse, then a central limit effect takes over and only two moments can be consistently estimated. We show that divergence of the sum of the…
谱密度估计的筛方法
We suggest a sieve for the estimation of the spectral density of a Gaussian stationary stochastic process. In contrast to the standard periodogram-based estimates this one aims at exploiting the full Gaussian nature of the process.