A Hidden Markov Model to Address Measurement Errors in Ordinal Response Scale and Non-Decreasing Process

A Hidden Markov Model to Address Measurement Errors in Ordinal Response Scale and Non-Decreasing Process

A Bayesian approach was developed, tested, and applied to model ordinal response data in monotone non-decreasing processes with measurement errors. An inhomogeneous hidden Markov model with continuous state-space was considered to incorporate measurement errors in the categorical response at the sam...

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Bibliographic Details
Main Authors: Lizbeth Naranjo, Luz Judith R. Esparza, Carlos J. Pérez
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Mathematics
Subjects:
Bayesian analysis
conditional independence
hidden Markov model
measurement error
misclassification
monotone continuous process
Online Access:https://www.mdpi.com/2227-7390/8/4/622

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https://www.mdpi.com/2227-7390/8/4/622

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