Nonlinear regime-switching state-space (RSSS) models

DOI10.1007/s11336-013-9330-8zbMath1288.62176OpenAlexW2078455547WikidataQ45927137 ScholiaQ45927137MaRDI QIDQ2452358

Guangjian Zhang, Sy-Miin Chow

Publication date: 2 June 2014

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-013-9330-8

zbMATH Keywords

state-spaceregime-switchingdynamic factor analysisKim filternonlinear latent variable models

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Related Items (7)

Bayesian forecasting with a regime-switching zero-inflated multilevel Poisson regression model: an application to adolescent alcohol use with spatial covariates ⋮ Forecasting intra-individual changes of affective states taking into account inter-individual differences using intensive longitudinal data from a university student dropout study in math ⋮ Control theory forecasts of optimal training dosage to facilitate children's arithmetic learning in a digital educational application ⋮ Estimation of nonlinear mixed‐effects continuous‐time models using the continuous‐discrete extended Kalman filter ⋮ Representing sudden shifts in intensive dyadic interaction data using differential equation models with regime switching ⋮ Fitting nonlinear ordinary differential equation models with random effects and unknown initial conditions using the stochastic approximation expectation-maximization (SAEM) algorithm ⋮ Zero-inflated regime-switching stochastic differential equation models for highly unbalanced multivariate, multi-subject time-series data

Uses Software

• GAUSS
• R
• SAS
• Mplus
• msm
• depmix
• OpenMx
• Ox
• PROC LTA

Cites Work

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