ESTIMATION AND INTERPOLATION OF MISSING VALUES OF A STATIONARY TIME SERIES

DOI10.1111/j.1467-9892.1989.tb00021.xzbMath0686.62067OpenAlexW2004514902MaRDI QIDQ4204971

Mohsen Pourahmadi

Publication date: 1989

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.1989.tb00021.x

zbMATH Keywords

EM-algorithmstationary time seriesautoregressive processmoving-average processinterpolating missing valuesmultistep-ahead predictorsprediction plus regression problem

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

Impact of missing data on the prediction of random fields, Optimization methods in time series interpolation, An optimal prediction in stationary random fields based on a new interpolation approach, Prediction of random fields with incomplete quarter-plane past, Prediction with incomplete past and interpolation of missing values, On recovery of discrete time signals with single-point spectrum degeneracy, Optimal linear interpolation of multiple missing values, Some prediction problems for stationary random fields with quarter-plane past, Unnamed Item, Duals of random vectors and processes with applications to prediction problems with missing values, Maximum likelihood estimation of the \(\mathrm{VAR}(1)\) model parameters with missing observations, Imputation-based semiparametric estimation for INAR(1) processes with missing data, A single-index model procedure for interpolation intervals in time series, Analysis of tidal data and datums: accessible examples of harmonic modeling with autocorrelation and imputation, Influence of Missing Values on the Prediction of a Stationary Time Series, On the estimation of missing values in AR(1) model with exponential innovations, A time series bootstrap procedure for interpolation intervals, Comparison of Two Estimation Methods of Missing Values Using Pitman-Closeness Criterion, Prediction of stationary Gaussian random fields with incomplete quarterplane past, Time series interpolation via global optimization of moments fitting

Cites Work

• Unnamed Item
• The prediction theory of multivariate stochastic processes. III: Unbounded spectral densities
• A matricial extension of the Helson-Szegö theorem and its application in multivariate prediction
• Best Approximations in L^p (d μ) and Prediction Problems of Szegö, Kolmogorov, Yaglom, and Nakazi
• Inverse Autocorrelations
• Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations
• The Inverse Autocorrelations of a Time Series and Their Applications
• A Duality Between Autoregressive and Moving Average Processes Concerning Their Least Squares Parameter Estimates
• Linear Statistical Inference and its Applications