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AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
Author(s) -
Shumway R. H.,
Stoffer D. S.
Publication year - 1982
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.1982.tb00349.x
Subject(s) - smoothing , estimator , series (stratigraphy) , mathematics , kalman filter , expectation–maximization algorithm , algorithm , maximum likelihood , simple (philosophy) , state space , time series , state space representation , mathematical optimization , econometrics , statistics , paleontology , philosophy , epistemology , biology
. An approach to smoothing and forecasting for time series with missing observations is proposed. For an underlying state‐space model, the EM algorithm is used in conjunction with the conventional Kalman smoothed estimators to derive a simple recursive procedure for estimating the parameters by maximum likelihood. An example is given which involves smoothing and forecasting an economic series using the maximum likelihood estimators for the parameters.