A General Framework for Longitudinal Data through Marked Point Processes

DOI10.1002/bimj.4710390107zbMath0894.60068OpenAlexW2063994946MaRDI QIDQ4353957

Thomas H. Scheike

Publication date: 31 August 1998

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.4710390107

zbMATH Keywords

longitudinal datamarked point processregression modelsweighted least squaresparametric inferenceconditional least squaresrepeated measure

Mathematics Subject Classification ID

Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (1)

A nonparametric dynamic additive regression model for longitudinal data.

Cites Work

• Nonparametric estimation of partial transition probabilities in multiple decrement models

This page was built for publication: A General Framework for Longitudinal Data through Marked Point Processes