Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R
Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are multiple parallel sequences per subject. Hidd...
Main Authors: | Satu Helske, Jouni Helske |
---|---|
Format: | Article |
Language: | English |
Published: |
Foundation for Open Access Statistics
2019-01-01
|
Series: | Journal of Statistical Software |
Subjects: | |
Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/2505 |
Similar Items
-
A Mixture Hidden Markov Model to Mine Students’ University Curricula
by: Silvia Bacci, et al.
Published: (2022-02-01) -
poLCA: An R Package for Polytomous Variable Latent Class Analysis
by: Drew A. Linzer, et al.
Published: (2011-08-01) -
How Do Art Skills Influence Visual Search? – Eye Movements Analyzed With Hidden Markov Models
by: Miles Tallon, et al.
Published: (2021-01-01) -
Efficient Bayesian generalized linear models with time-varying coefficients: The walker package in R
by: Jouni Helske
Published: (2022-06-01) -
Displaying Latent Classes in Figures: Consideration of Practices
by: Zhao, Xiang
Published: (2023-06-01)