Closure of linear processes

被引:17
作者
Bickel, PJ
Buhlmann, P
机构
[1] Department of Statistics, 367 Evans Hall #3860, University of California, Berkeley
关键词
AR process; infinitely divisible law; MA process; distinction from nonlinear process;
D O I
10.1023/A:1022616601841
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider the sets of moving-average and autoregressive processes and study their closures under the Mallows metric and the total variation convergence on finite dimensional distributions. These closures are unexpectedly large, containing nonergodic processes which are Poisson sums of i.i.d. copies From a stationary process. The presence of these nonergodic Poisson sum processes has immediate implications. In particular, identifiability of the hypothesis of linearity of a process is in question. A discussion of some of these issues for the set of moving-average processes has already been given without proof in Bickel and Buhlmann.((2)) We establish here the precise mathematical arguments and present some additional extensions: results about the closure of autoregressive processes and natural sub-sets of moving-average and autoregressive processes which are closed.
引用
收藏
页码:445 / 479
页数:35
相关论文
共 15 条
  • [1] Akamanam S. I., 1986, J TIME SER ANAL, V7, P157, DOI [10.1111/j.1467-9892.1986.tb00499.x, DOI 10.1111/J.1467-9892.1986.TB00499.X]
  • [2] SOME ASYMPTOTIC THEORY FOR THE BOOTSTRAP
    BICKEL, PJ
    FREEDMAN, DA
    [J]. ANNALS OF STATISTICS, 1981, 9 (06) : 1196 - 1217
  • [3] What is a linear process?
    Bickel, PJ
    Buhlmann, P
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1996, 93 (22) : 12128 - 12131
  • [4] Dunford N., 1957, PURE APPL MATH
  • [5] Durrett R., 2001, PROBABILITY THEORY E, Vthird
  • [6] GORODETSKII VV, 1977, THEOR PROBAB APPL+, V22, P411, DOI 10.1137/1122049
  • [7] HANNAN EJ, 1987, STAT SCI, V5, P105
  • [8] Hartigan J.A., 1983, BAYES THEORY
  • [9] KLEINER B, 1979, J ROY STAT SOC B MET, V41, P313
  • [10] Linnik Yu.V., 1964, Decomposition of Probability Distributions