Handling underlying discrete variables with bivariate mixed hidden Markov models in NONMEM

Non-linear mixed effects models typically deal with stochasticity in observed processes but models accounting for only observed processes may not be the most appropriate for all data. Hidden Markov models (HMMs) characterize the relationship between observed and hidden variables where the hidden var...

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Detalles Bibliográficos
Autores principales: Brekkan, A., Jönsson, S., Karlsson, M. O., Plan, E. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2019
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868114/
https://www.ncbi.nlm.nih.gov/pubmed/31654267
http://dx.doi.org/10.1007/s10928-019-09658-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868114/
https://www.ncbi.nlm.nih.gov/pubmed/31654267
http://dx.doi.org/10.1007/s10928-019-09658-z

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