Open AccessNon-Gaussian autoregressive moving average processes.
Author(s) -
K. S. Lii,
M. Rosenblatt
Publication year - 1993
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.90.19.9168
Subject(s) - autoregressive model , smoothness , gaussian , mathematics , star model , sequence (biology) , autoregressive–moving average model , moving average , stationary sequence , statistics , econometrics , autoregressive integrated moving average , statistical physics , stochastic process , mathematical analysis , time series , physics , biology , quantum mechanics , genetics
Non-Gaussian stationary autoregressive moving average sequences are considered. Under conditions concerning smoothness and positivity of the density function of the independent random variables generating the sequence, asymptotically efficient methods for the estimation of unknown coefficients of the model are described. The main interest is in nonminimum-phase models.
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