Windowed periodograms and moving average models

被引:0
|
作者
Broersen, PMT [1 ]
de Waele, S [1 ]
机构
[1] Delft Univ Technol, Dept Appl Phys, NL-2600 GA Delft, Netherlands
关键词
spectral estimation; order selection; spectral distance; spectral window; spectral error;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A windowed and tapered periodogram can be computed as the Fourier transform of an estimated covariance function of tapered data, multiplied by a lag window. Covariances of finite length can also be modeled as moving average (MA) time series models. The direct equivalence between periodograms and MA models is shown in the method of moments for MA estimation. A better MA representation for the covariance and the spectral density is found with Durbin's improved MA method. That uses the parameters of a long autoregressive (AR) model to find MA models, followed by automatic selection of the MA order. A comparison is made between the two MA model types. The best of many MA models from windowed periodograms is compared to the single selected MA model obtained with Durbin's method. The latter typically has a better quality.
引用
收藏
页码:2706 / 2709
页数:4
相关论文
共 50 条
  • [1] BOOTSTRAP IN MOVING AVERAGE MODELS
    BOSE, A
    ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 1990, 42 (04) : 753 - 768
  • [2] On buffered moving average models
    Zhuang, Yipeng
    Li, Dong
    Yu, Philip L. H.
    Li, Wai Keung
    JOURNAL OF TIME SERIES ANALYSIS, 2024,
  • [3] Critical value model of sample correlation coefficient after windowed moving average
    Lin, Haibo
    Chen, Li
    Zhao, Juan
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2018, 88 (18) : 3681 - 3693
  • [4] On moving-average models with feedback
    Li, Dong
    Ling, Shiqing
    Tong, Howell
    BERNOULLI, 2012, 18 (02) : 735 - 745
  • [5] Empirical likelihood for moving average models
    Li, Yinghua
    Qin, Yongsong
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2021, 50 (15) : 3661 - 3676
  • [6] Beta autoregressive moving average models
    Andréa V. Rocha
    Francisco Cribari-Neto
    TEST, 2009, 18 : 529 - 545
  • [7] Bayesian identification of moving average models
    Shaarawy, Samir M.
    Soliman, Emad E. A.
    Ali, Sherif S.
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2007, 36 (9-12) : 2301 - 2312
  • [8] Beta autoregressive moving average models
    Rocha, Andrea V.
    Cribari-Neto, Francisco
    TEST, 2009, 18 (03) : 529 - 545
  • [9] Bayesian Threshold Moving Average Models
    Smadi, Mahmoud M.
    Alodat, M. T.
    JOURNAL OF MODERN APPLIED STATISTICAL METHODS, 2011, 10 (01) : 262 - 267
  • [10] Generalized autoregressive moving average models
    Benjamin, MA
    Rigby, RA
    Stasinopoulos, DM
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2003, 98 (461) : 214 - 223