Moving-average representation of autoregressive approximations

被引:32
|
作者
Buhlmann, P
机构
[1] Department of Statistics, University of California, Berkeley, CA 94720, Evans Hall
关键词
AR(infinity); causal; complex analysis; impulse response function; invertible; linear process; MA(infinity); mixing; time series; transfer function; stationary process;
D O I
10.1016/0304-4149(95)00061-5
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 study the properties of an MA(infinity)-representation of an autoregressive approximation for a stationary, real-valued process. In doing so we give an extension of Wiener's theorem in the deterministic approximation setup. When dealing with data, we can use this new key result to obtain insight into the structure of MA(infinity)-representations of fitted autoregressive models where the order increases with the sample size. In particular, we give a uniform bound for estimating the moving-average coefficients via autoregressive approximation being uniform over ail integers.
引用
收藏
页码:331 / 342
页数:12
相关论文
共 50 条
  • [31] Engineering the nonlinear phase shift with multistage autoregressive moving-average optical filters
    Chen, Y
    Pasrija, G
    Farhang-Boroujeny, B
    Blair, S
    APPLIED OPTICS, 2005, 44 (13) : 2564 - 2574
  • [33] Wind-Tunnel Study of the Autoregressive Moving-Average Flutter Prediction Method
    Jidovetski, Tzlil Nahom
    Raveh, Daniella E.
    Iovnovich, Michael
    JOURNAL OF AIRCRAFT, 2019, 56 (04): : 1441 - 1454
  • [34] Measure of predictability of a stationary two dimensionally indexed autoregressive moving-average models
    Saidi, Amel
    Hamaz, Abdelghani
    Ibazizen, Mohamed
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2024, 53 (07) : 3170 - 3185
  • [35] Fuel cell performance prediction using an AutoRegressive Moving-Average ARMA model
    Detti, A. H.
    Yousfi-Steiner, N.
    Bouillaut, L.
    Same, A. B.
    Jemei, S.
    2019 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2019,
  • [36] On fractionally integrated autoregressive moving-average time series models with conditional heteroscedasticity
    Ling, SQ
    Li, WK
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1997, 92 (439) : 1184 - 1194
  • [37] Some Estimation Methods for a Random Coefficient in the Gegenbauer Autoregressive Moving-Average Model
    Essefiani, Oumaima
    El Halimi, Rachid
    Hamdoune, Said
    MATHEMATICS, 2024, 12 (11)
  • [39] Wind-tunnel study of the autoregressive moving-average flutter prediction method
    Jidovetski, Tzlil Nahom
    Raveh, Daniella E.
    Iovnovich, Michael
    Journal of Aircraft, 2019, 56 (04): : 1441 - 1454
  • [40] Statistical early-warning indicators based on autoregressive moving-average models
    Faranda, Davide
    Dubrulle, Berengere
    Pons, Flavio Maria Emanuele
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2014, 47 (25)