Methodologies for the estimation of missing observations in time series

DOI10.1016/0167-7152(87)90028-9zbMath0601.62109OpenAlexW2061824698MaRDI QIDQ1081262

Osvaldo Ferreiro

Publication date: 1987

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(87)90028-9

zbMATH Keywords

ARMAstationary time seriesKalman-Bucy filterautoregressive-moving averageestimation of missing observationsPEM algorithmpseudo-expectation maximization

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (5)

Optimization methods in time series interpolation ⋮ A Note on the Estimation of Missing Values in Time Series ⋮ Graphical and phase space models for univariate time series ⋮ A nonlinear time series model and estimation of missing observations ⋮ Influence of Missing Values on the Prediction of a Stationary Time Series

Cites Work

• Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Methodologies for the estimation of missing observations in time series