New Dynamic Predictive Monitoring Schemes Based on Dynamic Latent Variable Models
Sign Up to like & getrecommendations! Published in 2020 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.9b04741
Abstract: In this paper, dynamic predictive monitoring schemes based on dynamic latent variable models are proposed. We consider the most typical case in industrial data where dynamics usually exist in a red... read more here.
Keywords: based dynamic; dynamic latent; schemes based; predictive monitoring ... See more keywords
Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2025.2484011
Abstract: Abstract Model-based clustering of dynamic networks has emerged as an increasingly important research topic in statistical network analysis. Effectively and efficiently exploring the dynamic latent block structure of time-evolving networks is critical. We propose a… read more here.
Keywords: dynamic latent; family random; temporal exponential; exponential family ... See more keywords
Attention-Driven Supervised Dynamic Latent Variable Models for Monitoring Dynamic Industrial Process
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2025.3568934
Abstract: The accurate measurement and monitoring of quality variables are crucial for optimizing productivity and efficiency in industrial processes. However, many existing data-driven methods fail to account for the dynamic nature of industrial data and the… read more here.
Keywords: process; dynamic latent; attention driven; attention ... See more keywords
Are Bayesian regularization methods a must for multilevel dynamic latent variables models?
Sign Up to like & getrecommendations! Published in 2025 at "Behavior Research Methods"
DOI: 10.3758/s13428-024-02589-9
Abstract: Due to the increased availability of intensive longitudinal data, researchers have been able to specify increasingly complex dynamic latent variable models. However, these models present challenges related to overfitting, hierarchical features, non-linearity, and sample size… read more here.
Keywords: multilevel dynamic; dynamic latent; regularizing priors; bayesian regularization ... See more keywords