On Methods for Obtaining Asymptotically Efficient Spectral Parameter Estimates for a Stationary Gaussian Process with Rational Spectral Density

Previous article Next article On Methods for Obtaining Asymptotically Efficient Spectral Parameter Estimates for a Stationary Gaussian Process with Rational Spectral DensityK. O. DzhaparidzeK. O. Dzhaparidzehttps://doi.org/10.1137/1116061PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] I. A. Ibragimov, On maximum likelihood estimation of the spectral density parameters of a stationary process, Theory Prob. Applications, 12 (1967), 115–119 10.1137/1112013 LinkGoogle Scholar[2] K. O. Dzhaparidze, On the estimation of the spectral parameters of a stationary Gaussian process with rational spectral density, Theory Prob. Applications, 15 (1970), 531–538 10.1137/1115059 0221.62037 LinkGoogle Scholar[3] V. F. Pisarenko, Parameter bounds for a Gaussian stationary process with spectral density P(iλ ) -2, Litovsk. Mat. Sb., 2 (1962), 159–167, (In Russian.) MR0155384 Google Scholar[4] Harald Cramér, Mathematical Methods of Statistics, Princeton Mathematical Series, vol. 9, Princeton University Press, Princeton, N. J., 1946xvi+575 MR0016588 0063.01014 Google Scholar[5] K. C. Chanda, A note on the consistency and maxima of the roots of likelihood equations, Biometrika, 41 (1954), 56–61 MR0062997 0055.12901 CrossrefGoogle Scholar Previous article Next article FiguresRelatedReferencesCited ByDetails Locally Stationary ProcessesTime Series Analysis: Methods and Applications | 1 Jan 2012 Cross Ref An Alternative Perspective on Stochastic Coefficient Regression ModelsTime Series Analysis: Methods and Applications | 1 Jan 2012 Cross Ref Lévy–Driven Continuous–Time ARMA ProcessesHandbook of Financial Time Series | 10 February 2009 Cross Ref Continuous-time ARMA processesStochastic Processes: Theory and Methods | 1 Jan 2001 Cross Ref A likelihood approximation for locally stationary processesThe Annals of Statistics, Vol. 28, No. 6 | 1 Dec 2000 Cross Ref Asymptotically optimal estimation in misspecified time series modelsThe Annals of Statistics, Vol. 24, No. 3 | 1 Jun 1996 Cross Ref YULE-WALKER ESTIMATES FOR CONTINUOUS-TIME AUTOREGRESSIVE MODELSJournal of Time Series Analysis, Vol. 14, No. 3 | 1 May 1993 Cross Ref On Sufficient Statistics of Gaussian Processes with Rational Spectral Density FunctionTheory of Probability & Its Applications, Vol. 30, No. 1 | 28 July 2006AbstractPDF (900 KB)On Parameter Estimation in the Presence of NoiseTheory of Probability & Its Applications, Vol. 29, No. 3 | 17 July 2006AbstractPDF (638 KB)On Parameter Estimation by the Davidon–Fletcher–Powell MethodTheory of Probability & Its Applications, Vol. 27, No. 2 | 17 July 2006AbstractPDF (723 KB)Structural parameter estimation in power systemsAutomatica, Vol. 17, No. 2 | 1 Mar 1981 Cross Ref Parameter Estimation of Continuous-Time Linear Systems by Fitting Autocorrelation Functions with Application to Power System Structural Parameter EstimationIFAC Proceedings Volumes, Vol. 11, No. 1 | 1 Jan 1978 Cross Ref Some Problems in the Identification and Estimation of Continuous time Systems from Discrete time SeriesSystem Identification Advances and Case Studies | 1 Jan 1976 Cross Ref On Simplified Estimators of Unknown Parameters with Good Asymptotic PropertiesTheory of Probability & Its Applications, Vol. 19, No. 2 | 28 July 2006AbstractPDF (1036 KB)A New Method for Estimating Spectral Parameters of a Stationary Regular Time SeriesTheory of Probability & Its Applications, Vol. 19, No. 1 | 28 July 2006AbstractPDF (928 KB)Radon-Nikodym derivatives in case of rational spectral densitiesStochastic Differential Systems Cross Ref Volume 16, Issue 3| 1971Theory of Probability & Its Applications History Submitted:01 December 1969Published online:17 July 2006 InformationCopyright © Society for Industrial and Applied MathematicsPDF Download Article & Publication DataArticle DOI:10.1137/1116061Article page range:pp. 550-554ISSN (print):0040-585XISSN (online):1095-7219Publisher:Society for Industrial and Applied Mathematics