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CONTINUOUS‐TIME DYNAMICAL SYSTEMS WITH SAMPLED DATA, ERRORS OF MEASUREMENT AND UNOBSERVED COMPONENTS
Author(s) -
Singer Hermann
Publication year - 1993
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.1467-9892.1993.tb00162.x
Subject(s) - mathematics , maximum likelihood , observational error , estimation , statistics , algorithm , mathematical optimization , management , economics
. Maximum likelihood estimation of sampled continuous‐time stochastic processes is considered. The likelihood is directly maximized with respect to the original structural parameters using a scoring algorithm with exact analytical derivatives. Furthermore, the case of unobserved states and errors of measurement is treated via EM and quasi‐Newton algorithms. The proposed methods are illustrated with simulation studies and analysis of sunspot activity.