两类广义预测控制算法的统一推广

基于ＣＡＲＩＭＡ模型和ＡＲＭＡＸ模型的广义预测控制算法是两类基本的ＧＰＣ算法，给出了它们的统一格式，对ＧＰＣ算法的理论分析和实际应用有意义。     

An Alternative to Transfer Function Forecasting Based on Subspace Methods

In the time series literature, recent interest has focused on the so-called subspace methods. These techniques use canonical correlations and linear regressions to estimate the system matrices of an ARMAX model expressed in state space form. In this article, we use subspace methods to forecast two series with the help of some exogenous variables related to them. We compare the results with those obtained using traditional transfer function models and find that the forecasts obtained with both methods are similar. This result is very encouraging because, in contrast to transfer function models, subspace methods can be considered as almost automatic.     

准EL算法下ARMAX模型的阶估计

本文给出了一种推广的 BIC 准则,根据对准 EL 算法的估计和对 ARMAX 模型变形后的全项f_(n 1)的估计所得到的有关结果,讨论了一种确定 ARMAX 模型阶数的方法。并给出了在推广的BIC 准则意义下关于 ARMAX 模型阶数的最优估计和阶估计的收敛性。同时,也得到了该模型系数矩阵估计的收敛性和收敛速度。     

Kernel Likelihood Inference for Time Series

Abstract.  This paper develops non-parametric techniques for dynamic models whose data have unknown probability distributions. Point estimators are obtained from the maximization of a semiparametric likelihood function built on the kernel density of the disturbances. This approach can also provide Kullback–Leibler cross-validation estimates of the bandwidth of the kernel densities. Confidence regions are derived from the dual-empirical likelihood method based on non-parametric estimates of the scores. Limit theorems for martingale difference sequences support the statistical theory; moreover, simulation experiments and a real case study show the validity of the methods.     

The relation between unemployment and interest rate:

In bierens (1987) a granger casual relation was found between unemployment and the interest rate for the netherlands. In the present paper we will investigate whether there exists a similar granger casual relation between unemployment and interest rate for a number of other countries. It appears that, with our ARMAX modeling approach, this relationship is not confined to the netherlands, but also holds for the USA, Canada, Japan, Germany, the UK and France. For these countries the interest rate is the main explanatory variable, together with industrial production (the latter with one exception), whereas for most countries the wage rate is of minor or no importance as a determinant of unemployment. A number of economic theories can explain these phenomena of which the revenue maximization theory of baumol (1959) augmented with a flexible labor effort rate seems quite realistic     

Cellular automata and Riccati equation models for diffusion of innovations

Innovation diffusion represents a central topic both for researchers and for managers and policy makers. Traditionally, it has been examined using the successful Bass models (BM, GBM), based on an aggregate differential approach, which assures flexibility and reliable forecasts. More recently, the rising interest towards adoptions at the individual level has suggested the use of agent based models, like Cellular Automata models (CA), that are generally implemented through computer simulations. In this paper we present a link between a particular kind of CA and a separable non autonomous Riccati equation, whose general structure includes the Bass models as a special case. Through this link we propose an alternative to direct computer simulations, based on real data, and a new aggregate model, which simultaneously considers birth and death processes within the diffusion. The main results, referred to the closed form solution, the identification and the statistical analysis of our new model, may be both of theoretical and empirical interest. In particular, we examine two applied case studies, illustrating some forecasting improvements obtained.