SEM Modeling with Singular Moment Matrices Part I: ML-Estimation of Time Series

DOI10.1080/0022250X.2010.509524zbMath1202.62124MaRDI QIDQ3063869

Hermann Singer

Publication date: 15 December 2010

Published in: The Journal of Mathematical Sociology (Search for Journal in Brave)

zbMATH Keywords

estimationtime seriesstate space modelsmaximum likelihood (ML)Kalman filtering (KF)structural equation models (SEM)

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (5)

SEM Modeling with Singular Moment Matrices Part II: ML-Estimation of Sampled Stochastic Differential Equations ⋮ Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms ⋮ Representing sudden shifts in intensive dyadic interaction data using differential equation models with regime switching ⋮ SEM modeling with singular moment matrices Part III: GLS estimation ⋮ Zero-inflated regime-switching stochastic differential equation models for highly unbalanced multivariate, multi-subject time-series data

Uses Software

• LSDE

Cites Work

• Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models
• Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes
• Stochastic processes and filtering theory
• CONTINUOUS-TIME DYNAMICAL SYSTEMS WITH SAMPLED DATA, ERRORS OF MEASUREMENT AND UNOBSERVED COMPONENTS
• Evaluation of likelihood functions for Gaussian signals
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