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向量自回归与宏观经济建模：误差分类AI 解读

In this article, we investigate the theoretical behavior of finite lag VAR(n)$\text{VAR}(n)$ models fitted to time series that in truth come from an infinite-order VAR(∞)$\text{VAR}(\infty)$ data-generating mechanism. We show that the overall error can be broken down into two basic components, an estimation error that stems from the difference between the parameter estimates and their population ensemble VAR(n)$\text{VAR}(n)$ counterparts, and an approximation error that…

用预滤波筛自助法修正半参数长记忆估计偏差AI 解读

This paper investigates bootstrap-based bias correction of semiparametric estimators of the long memory parameter, d , in fractionally integrated processes. The re-sampling method involves the application of the sieve bootstrap to data prefiltered by a preliminary semiparametric estimate of the long memory parameter. Theoretical justification for using the bootstrap technique to bias adjust log periodogram and semiparametric local Whittle estimators of the memory parameter…

This paper provides the practitioner with a method of ascertaining when the concentration parameter in a simultaneous equations model is small. We provide some exact distribution theory for a proposed statistic and show that the statistic possesses the minimal desirable characteristics of a test statistic when used to test that the concentration parameter is zero. The discussion is then extended to consider how to test for weak instruments using this statistic as a basis for…

基于典型相关的协整秩强一致判定AI 解读

This article is concerned with the statistical analysis of nonstationary, cointegrated time series. The estimation of the cointegrating structure of such time series is considered, and the problem of identifying the cointegrating rank is addressed. A methodology is presented that leads to strongly consistent estimates of this quantity. The identification is based on a canonical correlation analysis of the original variables and presents an alternative approach to those…

双盲反卷积：神经细胞突触后电流的分析AI 解读

Summary This paper is concerned with the analysis of observations made on a system that is being stimulated at fixed time intervals but where the precise nature and effect of any individual stimulus is unknown. The realized values are modelled as a stochastic process consisting of a random signal embedded in noise. The aim of the analysis is to use the data to unravel the unknown structure of the system and to ascertain the probabilistic behaviour of the stimuli. A method of…

阶梯形 VARMA 模型的设定AI 解读

The echelon form of a vector autoregressive moving average (VARMA) model is considered. Its advantages over other identified VARMA representations are discussed. Furthermore, a general strategy for specifying echelon form VARMA models from data is presented. Specifically, procedures for choosing the Kronecker indices that characterize an echelon form are reviewed. The feasibility of the method is demonstrated by analyzing a well-known set of flour price time series and the…

基于周期图的分形性质估计量AI 解读

We suggest an estimator, based on the periodogram, of the fractal index and fractal dimension of a continuous, stationary Gaussian process. We argue that the cosine part of the periodogram is more appropriate than the full periodogram for this application. The term "semiperiodogram" is used to describe the cosine component, and our estimator is based on simple linear regression of the logarithm of the semiperiodogram on the algorithm of frequency. Theoretical properties of…

用最小二乘识别向量线性过程的阶梯规范形式AI 解读

In this paper a method of identifying stationary and invertible vector autoregressive moving-average time series is proposed. The models are presumed to be represented in (reversed) echelon canonical form. Consideration is given to both parameter estimation and the determination of structural indices, the evaluations being based on the use of closed form least squares calculations. Consistency of the technique is shown and the operational characteristics of the procedure…

摘要暂缺

传递函数模型的估计与识别方法AI 解读

SUMMARY This paper proposes an approach to the simultaneous identification and estimation of transfer function models. An estimation procedure is advanced consisting of a sequence of four ordinary least squares calculations and the asymptotic properties of each step are presented, consistency and asymptotic efficiency being shown. A strategy for the identification of the model structure based on a selection criterion that arises naturally from the last step of the estimation…

自回归频率估计AI 解读

Presume that an autoregressive model of given order is fitted to data obtained from a realization of a sinusoidal signal embedded in white noise. This paper investigates the statistical properties of the estimate of the frequency of the signal obtained by minimizing the transfer function of the autoregression. Strong consistency and convergence in distribution of the estimate are established when the order of the autoregression is allowed to increase with sample size at an…

自回归模型的递归估计AI 解读

SUMMARY This paper is concerned with the recursive estimation of autoregressive models, in particular the realtime determination of the order of such a specification. A model selection criterion based on the minimum description length principle due to Rissanen is discussed and strong consistency in the stationary situation is shown. Alternative criteria are also considered and modifications required to introduce forgetting when the procedures are implemented in the…

自回归频率估计AI 解读

Presume that an autoregressive model of given order is fitted to data obtained from a realization of a sinusoidal signal embedded in white noise. This paper investigates the statistical properties of the estimate of the frequency of the signal obtained by minimizing the transfer function of the autoregression. Strong consistency and convergence in distribution of the estimate are established when the order of the autoregression is allowed to increase with sample size at an…

未来与过去之间的单位典型相关AI 解读

Stationary vector ARMA processes $x(t), t = 0, \pm 1, \pm 2, \cdots$, of $n$ components are considered that are of full rank, and the situation where there are linear functions of the future $x(t), t > 0$, and the past $x(t), t \leq 0$ (more properly the present and the past) that have unit correlation. It is shown that the number of linearly independent such pairs (i.e., the number of unit canonical correlations between future and past) is the number of zeros of the…

摘要暂缺

构建线性时间序列模型的候选集合AI 解读

The paper applies selection criteria to order determination in linear time series models in a less mechanical fashion than is often found. This is achieved via posterior odds ratios and by applying concepts of grades of evidence advanced by Jeffreys (1961). It is shown how alternative specifications may be compared and this leads to the development of a practical method for determining a portfolio of different models, each of which may be regarded as reasonable for the data…

精度、复杂度与贝叶斯模型确定AI 解读

SUMMARY In this paper a new criterion for model determination is proposed. An explicit decision theoretic approach to model selection is employed to derive a Bayes decision rule. The operational characteristics of the criterion are discussed and consistency is shown.

混合 ARMA 阶数确定的修正 Hannan—Rissanen 策略AI 解读

A modification to the model selection strategy for mixed autoregressive-moving average order determination suggested by Hannan & Rissanen (1982) is proposed. The modification is designed to eliminate the bias discussed by Hannan & Kavalieris (1984) and involves the use of an alternative model selection criterion. Asymptotic properties of the modified procedure are established and some simulation evidence on the finite sample performance is provided.

确定线性时间序列模型的候选集合AI 解读

The paper applies selection criteria to order determination in linear time series models in a less mechanical fashion than is often found. This is achieved via posterior odds ratios and by applying concepts of grades of evidence advanced by Jeffreys (1961). It is shown how alternative specifications may be compared and this leads to the development of a practical method for determining a portfolio of different models, each of which may be regarded as reasonable for the data…

单变量时间序列模型识别的贝叶斯程序AI 解读

This paper is concerned with model selection in time series analysis. An identification criterion is presented that is asymptotically equivalent to a Bayes decision rule. The discussion is conducted in the context of a general class of parametric time series models and consideration is given to the special case of order determination in autoregressive moving-average representations. Consistency of the criterion is proved.

含外生变量的向量时间序列模型误设检验AI 解读

SUMMARY In this paper we consider the application of hypothesis testing procedures to ARMAX systems. The score, or Lagrangian multiplier, principle is used to obtain mis-specification tests appropriate to these models. The structure of the information or sensitivity matrix is investigated in order to discuss the identifiability of alternative models and is used to show the existence of a set of admissible alternatives that are locally equivalent to one another. This notion…

时间序列模型的后验赔率AI 解读

This paper is concerned with model selection in time series analysis. A Bayesian approach is adopted to investigate various decision criteria previously advocated. The discussion is conducted in the context of a class of nonlinear time series models of sufficient generality to encompass a wide range of processes currently of interest.

时间序列模型的后验赔率AI 解读

This paper is concerned with model selection in time series analysis. A Bayesian approach is adopted to investigate various decision criteria previously advocated. The discussion is conducted in the context of a class of nonlinear time series models of sufficient generality to encompass a wide range of processes currently of interest.

多元时间序列模型的诊断检验AI 解读

This paper is concerned with the development and application of diagnostic checks for vector linear time series models. A hypothesis testing procedure based upon the score, or Lagrangean multiplier, principle is advocated and the distributions of the test statistic both under the null hypothesis and under a Pitman sequence of alternatives are discussed. Consideration of alternative models with singular sensitivity matrices when the null hypothesis is true leads to an…