Computation of the exact information matrix of Gaussian dynamic regression time series models

DOI10.1214/aos/1024691256zbMath0929.62094OpenAlexW2071973071MaRDI QIDQ1807120

Toufik Zahaf, Guy Mélard, Andre Klein

Publication date: 9 November 1999

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1024691256

zbMATH Keywords

information matrixChandrasekhar equationsSISO models

Mathematics Subject Classification ID

Related Items (6)

A New Recursive Estimation Method for Single Input Single Output Models ⋮ Computing the Exact Fisher Information Matrix of Periodic State-Space Models ⋮ An algorithm for computing the asymptotic fisher information matrix for seasonal SISO models ⋮ Calculation of the Fisher Information Matrix for Periodic ARMA Models ⋮ Construction of the exact Fisher information matrix of Gaussian time series models by means of matrix differential rules ⋮ On the Evaluation of the Information Matrix for Multiplicative Seasonal Time-Series Models

Uses Software

• AS 197

Cites Work

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• Some efficient computational procedures for high order ARMA models
• Asymptotic Distributions of Impulse Responses, Step Responses, and Variance Decompositions of Estimated Linear Dynamic Models
• Algorithm AS 197: A Fast Algorithm for the Exact Likelihood of Autoregressive-Moving Average Models
• FISHER'S INFORMATION MATRIX FOR SEASONAL AUTOREGRESSIVE-MOVING AVERAGE MODELS
• Evaluation of the covariance matrix for the maximum likelihood estimator of a Gaussian autoregressive-moving average process
• On the computation of the Cramer-Rao bound for ARMA parameter estimation
• Computing the likelihood and its dierivatives for a gaussian ARMA model
• Cramer-Rao bounds for AR parameter and reflection coefficient estimators
• The Euclid algorithm and the fast computation of cross-covariance and autocovariance sequences
• Some new algorithms for recursive estimation in constant, linear, discrete-time systems

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