A Note on the Estimation of Missing Values in Time Series

DOI10.1080/03610918908812770zbMath0695.62213OpenAlexW1972593352MaRDI QIDQ3471562

Greta M. Ljung

Publication date: 1989

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918908812770

zbMATH Keywords

interpolationoutlierstime serieslikelihood functionmissing valuesautoregressive moving average process

Mathematics Subject Classification ID

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

Related Items

A note on interpolation of arima processes, Optimization methods in time series interpolation, A recursive approach for estimating missing observations in an univariate time series, A single-index model procedure for interpolation intervals in time series, Genetic algorithms for the identification of additive and innovation outliers in time series, A time series bootstrap procedure for interpolation intervals, Missing observations in ARIMA models: Skipping approach versus additive outlier approach, Time series interpolation via global optimization of moments fitting

Cites Work

• Methodologies for the estimation of missing observations in time series
• INVERSE AUTOCOVARIANCES AND A MEASURE OF LINEAR DETERMINISM FOR A STATIONARY PROCESS
• Estimation, Prediction, and Interpolation for ARIMA Models with Missing Data
• Estimation of the interpolation error variance and an index of linear determinism
• Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations
• The likelihood function of stationary autoregressive-moving average models