Maximum likelihood estimation for continuous-time autoregressive models by relaxation on residual variances ratio parameters

DOI10.1007/BF01213470zbMath0780.93071OpenAlexW2072131763MaRDI QIDQ1802201

Pham Dinh Tuan, Alain Le Breton

Publication date: 26 January 1994

Published in: MCSS. Mathematics of Control, Signals, and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01213470

zbMATH Keywords

iterative algorithmmaximum likelihood estimatorcontinuous-timecontinuous-time autoregressive model

Mathematics Subject Classification ID

Stochastic systems in control theory (general) (93E03) Model systems in control theory (93C99)

Cites Work

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• Levinson-Durbin-type algorithms for continuous-time autoregressive models and applications
• On the parametrization of autoregressive models by partial autocorrelations
• A Strong Limit Theorem for Gaussian Processes
• The Fitting of Time-Series Models
• Recursive maximum likelihood estimation of autoregressive processes
• On Sufficient Statistics of Gaussian Processes with Rational Spectral Density Function
• Maximum likelihood estimation of the autoregressive model by relaxation on the reflection coefficients
• A Levinson-type algorithm for modeling fast-sampled data
• Autoregressive estimation using residual energy ratios (Corresp.)
• On linear statistical problems in stochastic processes

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