On Rissanen's predictive stochastic complexity for stationary ARMA processes

DOI10.1016/0378-3758(94)90026-4zbMath0816.62072OpenAlexW2082745970WikidataQ127351634 ScholiaQ127351634MaRDI QIDQ1338377

László Gerencsér

Publication date: 3 July 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)90026-4

zbMATH Keywords

regretstationary ARMA processesrecursive prediction error estimator\(L\)-mixing processesalmost sure asymptotic propertiesARMA parametersreduced predictive stochastic complexityRissanen Shannon inequality

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical aspects of information-theoretic topics (62B10)

Related Items (8)

On Rissanen's predictive stochastic complexity for stationary ARMA processes ⋮ On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case ⋮ Rate of convergence of the LMS method ⋮ Nonparametric sequential prediction of time series ⋮ An Open Problem on Strongly Consistent Learning of the Best Prediction for Gaussian Processes ⋮ Accumulative prediction error and the selection of time series models ⋮ On fixed gain recursive estimators with discontinuity in the parameters ⋮ Strong approximation of the recursive prediction error estimator of the parameters of an ARMA process

Cites Work

• On covariance function tests used in system identification
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• On Rissanen's predictive stochastic complexity for stationary ARMA processes
• Relations between information criteria for model-structure selection Part 3. Strong consistency of the predictive least squares criterion
• On a class of mixing processes
• Rate of Convergence of Recursive Estimators
• Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model
• THE ESTIMATION OF THE ORDER OF AN AUTOREGRESSION USING RECURSIVE RESIDUALS AND CROSS-VALIDATION
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