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A NONSTATIONARY TIME SERIES MODEL AND ITS FITTING BY A RECURSIVE FILTER
Author(s) -
Kitagawa Genshiro
Publication year - 1981
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.1467-9892.1981.tb00316.x
Subject(s) - mathematics , series (stratigraphy) , state space , representation (politics) , state space representation , filter (signal processing) , square root , state (computer science) , maximum likelihood , time series , process (computing) , estimation , algorithm , statistics , mathematical optimization , econometrics , computer science , paleontology , political science , law , operating system , management , economics , computer vision , biology , geometry , politics
. The use of the state space representation for the analysis of nonstationary time series is proposed. For the fitting of the models, the use of a modified AIC based on the likelihood of the innovation process is proposed. A square root filter/smoother algorithm for the evaluation of the likelihood and state estimation is discussed.