摘要:

Abstract.The theory of state‐dependent models was developed by Priestley (1980), and a few simple applications were given in Priestley (1981). In this paper, an extensive study of the application of state‐dependent models to a wide variety of non‐linear time series data is carried out. Both real and simulated data are used in the study, and the problems encountered are highlighted. The method is demonstrated to be successful in practice in many cases, and suggestions for the further development of the algorithm are also

ISSN:0143-9782    

DOI:10.1111/j.1467-9892.1984.tb00379.x

出版商:Blackwell Publishing Ltd    

年代:1984

数据来源: WILEY

摘要:

Abstract.The estimation of subset autoregressive time series models has been a difficult problem because of the large number of possible alternative models involved. However, with the advent of model selection criteria based on the maximum likelihood, subset model fitting has become feasible. Using an efficient technique for evaluating the residual variance of all possible subset models, a method is proposed for the fitting of subset autoregressive models. The application of the method is illustrated by means of real and simulated data.

ISSN:0143-9782    

DOI:10.1111/j.1467-9892.1984.tb00380.x

出版商:Blackwell Publishing Ltd    

年代:1984

数据来源: WILEY

摘要:

Abstract.This paper deals with order determination of multivariate time series where roots of the characteristic equation are allowed to be equal to one. For estimation of parameters in such processes, least squares were used. For a familiar class of order determination criteria it is shown that results on weak consistency valid in the stationary case can be generalized to processes with unit roots in the characteristic equation. Then a discussion of the possibility of underestimating the order for finite samples is given for a particular model, and it is indicated that nonstationarity of this type decreases the probability of underestimating the order. Finally some Monte Carlo simulation results are given to supplement the theoretical results.

ISSN:0143-9782    

DOI:10.1111/j.1467-9892.1984.tb00381.x

出版商:Blackwell Publishing Ltd    

年代:1984

数据来源: WILEY

摘要:

Abstract.This paper considers the class of ARMA models with ARCH errors. Maximum Likelihood and Least Squares estimates of the parameters of the model and their covariance matrices are noted and incorporated into techniques for model building based upon the application of the usual Box‐Jenkins methodology of identification, estimation and diagnostic checking to the ARMA equation, the ARCH equation, and the full model. The techniques are applied to 16 U.S. macroeconomic time series and it is seen that in many of the series, models from this class can be constructe

ISSN:0143-9782    

DOI:10.1111/j.1467-9892.1984.tb00382.x

出版商:Blackwell Publishing Ltd    

年代:1984

数据来源: WILEY