Asymptotically optimal estimation of MA and ARMA parameters of non-Gaussian processes from high-order moments

DOI10.1109/9.45140zbMath0713.62086OpenAlexW2106382018MaRDI QIDQ3198751

Boaz Porat, Benjamin Friedlander

Publication date: 1990

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/9.45140

zbMATH Keywords

moving averageautoregressive moving averagenon-Gaussian processescovariancessample momentsARMA parametersasymptotically minimum variance algorithmcross-covariancessample high- order momentsweighted least-squares algorithms

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09)

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Identification of linear systems with noisy input using input-output cumulants ⋮ Third-order cumulants based methods for continuous-time errors-in-variables model identification ⋮ Maximum likelihood estimation for non-minimum-phase noise transfer function with Gaussian mixture noise distribution ⋮ Blind channel identification from burst data using implicit matching of HOS ⋮ Blind identification of MISO-FIR channels ⋮ Estimating the mean and its effects on Neyman smooth tests of normality for ARMA models

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