Forecasting with incomplete data

DOI10.1080/03610929508831551zbMath0850.62689OpenAlexW1995972887MaRDI QIDQ4883443

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Publication date: 4 July 1996

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929508831551

zbMATH Keywords

missing observationsforecastingstate space representationKalman filter algorithm

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Bayesian inference (62F15)

Related Items (1)

An Adaptive Extended Kalman Filter with Application to Compartment Models

Cites Work

• Unnamed Item
• Covariance matrix computation of the state variable of a stationary Gaussian process
• Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes
• Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations
• An algorithm for the exact likelihood of a mixed autoregressive-moving average process
• Some new algorithms for recursive estimation in constant, linear, discrete-time systems

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