Bayesian Estimation of Hierarchical Linear Models From Incomplete Data: Cluster‐Level Interaction Effects and Small Sample Sizes
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DOI: 10.1002/sim.70051
Abstract: We consider Bayesian estimation of a hierarchical linear model (HLM) from partially observed data, assumed to be missing at random, and small sample sizes. A vector of continuous covariates C$$ C $$ includes cluster‐level partially… read more here.
Keywords: estimation hierarchical; bayesian estimation; small sample; estimation ... See more keywords
Nonparametric Density Estimation of Hierarchical Probabilistic Graph Models for Assumption-Free Monitoring
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DOI: 10.1021/acs.iecr.6b04068
Abstract: Probabilistic graphical models, such as Bayesian networks, have recently gained attention in process monitoring and fault diagnosis. Their application, however, is limited to discrete or continuous Gaussian distributed variables, which results from the difficulty in… read more here.
Keywords: estimation; hierarchical probabilistic; density estimation; density ... See more keywords