A Variational Approach to Continuous Time Dynamic Models

Hannes Meinlschmidt (), Meike Sons () and Mark Stemmler ()
Additional contact information
Hannes Meinlschmidt: Department of Mathematics, Chair for Dynamics, Control, Machine Learning and Numerics (AvH-Professorship), FAU Erlangen-Nürnberg
Meike Sons: Arbeitsmedizinisches Institut für Schulen (AMIS-Bayern), Bayerisches Landesamt für Gesundheit und Lebensmittelsicherheit
Mark Stemmler: Friedrich-Alexander-University of Erlangen-Nuremberg (FAU), Institute of Psychology

Chapter Chapter 5 in Dependent Data in Social Sciences Research, 2024, pp 107-125 from Springer

Abstract: Abstract In this chapter we introduce a new approach to parameter estimation in continuous time modeling in the spirit of variational data assimilation or machine learning. This is a purely time-continuous approach relying on the theory of optimization for dynamical systems. We complement the proposed algorithm with a practical example, comparing the results of this approach to those obtained via Continuous Time Structural Equation Modeling (ctsem). To this end, we assess the reciprocal relationship between satisfaction with health and satisfaction with work using data from the German Socio-Economic Panel. It turns out that the proposed algorithm determines a drift matrix whose principle directions (eigenvectors) are qualitatively equivalent to the ones estimated via ctsem, but the associated eigenvalues differ substantially, leading to quantitatively different conclusions.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-56318-8_5

Ordering information: This item can be ordered from
http://www.springer.com/9783031563188

DOI: 10.1007/978-3-031-56318-8_5

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().