REFINED INSTRUMENTAL VARIABLE METHODS OF RECURSIVE TIME-SERIES ANALYSIS .2. MULTIVARIABLE SYSTEMS

被引:59
作者
JAKEMAN, A
YOUNG, P
机构
[1] Centre for Resource and Environmental Studies, Australian National University, Canberra
关键词
D O I
10.1080/00207177908922724
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper describes the refined IVAML algorithm for estimating the parameters in the multiveriable analogue of the single input., single output model considered in Part 1. It also shows that similar refined algorithms can be constructed for other multivariable model forms, including the ARMAX, dynamic adjustment (DA) with autoregressive errors and the multivariable transfer function (MTF). The perform. ance of the algorithm is evaluated by Monte Carlo analysis applied to four simulation models with between 25 and 39 parameters and it is carried out for various sample sizes and signal/noise ratios. As in the 8180 model version, the analysis indicates that the algorithm yields asymptotically efficient estimation results, whilst providing low variance estimates of the basic system parameters for medium sample sizes. © 1979 Taylor & Francis Group, LLC.
引用
收藏
页码:621 / 644
页数:24
相关论文
共 32 条
  • [1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION
    AKAIKE, H
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) : 716 - 723
  • [2] ASTROM KJ, 1965, THEORY SELF ADAPTIVE
  • [3] BECK B, 1976, J ENV ENG DIV-ASCE, V102, P909
  • [4] BOX GEP, 1970, TIME SERIES ANAL FOR
  • [5] DHRYMES PJ, 1970, ECONOMETRICS
  • [6] GOODWIN GC, 1975, SYSTEM IDENTIFICATIO
  • [7] CONVERGENCE OF SOME RECURSIONS
    HANNAN, EJ
    [J]. ANNALS OF STATISTICS, 1976, 4 (06) : 1258 - 1270
  • [8] Hendry D.F., 1976, J ECONOMETRICS, V4, P51, DOI DOI 10.1016/0304-4076(76)90017-8
  • [9] Hendry D.F., 1974, J ECONOMETRICS, V2, P151
  • [10] HOLST J, 1977, LUTFD2TRFT10131206 L