The following pages link to Label.switching (Q26642):
Displaying 21 items.
- On the identifiability of Bayesian factor analytic models (Q113012) (← links)
- Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components (Q140405) (← links)
- Overfitting Bayesian mixtures of factor analyzers with an unknown number of components (Q140406) (← links)
- A Bayesian approach to modeling group and individual differences in multidimensional scaling (Q256396) (← links)
- Importance sampling schemes for evidence approximation in mixture models (Q516488) (← links)
- Post-processing of Markov chain Monte Carlo output in Bayesian latent variable models with application to multidimensional scaling (Q722742) (← links)
- Bayesian Plackett-Luce mixture models for partially ranked data (Q1695638) (← links)
- Relabelling in Bayesian mixture models by pivotal units (Q1704029) (← links)
- Direct estimation of diagnostic classification model attribute mastery profiles via a collapsed Gibbs sampling algorithm (Q2103572) (← links)
- A Gibbs sampling algorithm with monotonicity constraints for diagnostic classification models (Q2129301) (← links)
- Anchored Bayesian Gaussian mixture models (Q2209835) (← links)
- Model-based approach to the joint analysis of single-cell data on chromatin accessibility and gene expression (Q2218013) (← links)
- Bayesian subgroup analysis in regression using mixture models (Q2242036) (← links)
- Identifying the recurrence of sleep apnea using a harmonic hidden Markov model (Q2247460) (← links)
- Bayesian cylindrical data modeling using Abe-Ley mixtures (Q2307289) (← links)
- Bayesian variable selection in linear regression models with non-normal errors (Q2324308) (← links)
- (Q4558478) (← links)
- Spatial modeling of brain connectivity data via latent distance models with nodes clustering (Q4970244) (← links)
- MCMC for Markov-switching models—Gibbs sampling vs. marginalized likelihood (Q5082562) (← links)
- Word distinctivity -- quantifying improvement of topic modeling results from \(n\)-gramming (Q5091894) (← links)
- PLMIX: an <tt>R</tt> package for modelling and clustering partially ranked data (Q5107752) (← links)
