The Mixturegram: A Visualization Tool for Assessing the Number of Components in Finite Mixture Models
From MaRDI portal
Publication:3391089
DOI10.1080/10618600.2017.1398093OpenAlexW2767337968MaRDI QIDQ3391089
Derek S. Young, Xiaoxue Zeng, Chenlu Ke
Publication date: 28 March 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10618600.2017.1398093
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Root selection in normal mixture models
- Mixtures of linear regressions
- Mixtures of regressions with changepoints
- Bayesian regularization for normal mixture estimation and model-based clustering
- Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
- Estimating the dimension of a model
- Determination of paths to vendor market effciency using parallel coordinates representation: A negotiation tool for buyers
- The plane with parallel coordinates
- Bayesian analysis of mixture models with an unknown number of components\,--\,an alternative to reversible jump methods.
- Visualizing non-hierarchical and hierarchical cluster analysis with clustergrams
- Empirical identifiability in finite mixture models
- Assessment of the number of components in Gaussian mixture models in the presence of multiple local maximizers
- Cluster Analysis
- Mixture Densities, Maximum Likelihood and the EM Algorithm
- On Using Principal Components Before Separating a Mixture of Two Multivariate Normal Distributions
- Modelling Change in Cognitive Understanding with Finite Mixtures
- The EM Algorithm and Extensions, 2E
- Statistical analysis of finite mixture distributions
- Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model
- A Graphical Technique for Determining the Number of Components in a Mixture of Normals
- Estimating the Propagation Rate of a Viral Infection of Potato Plants via Mixtures of Regressions
- Dealing With Label Switching in Mixture Models
- Finite mixture models
- A NONPARAMETRIC BAYESIAN APPROACH TO DETECT THE NUMBER OF REGIMES IN MARKOV SWITCHING MODELS
- Bayesian Density Estimation and Inference Using Mixtures
- Parametric Estimation in a Genetic Mixture Model with Application to Nuclear Family Data
- Random effects regression mixtures for analyzing infant habituation
- The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes
- Avoiding spurious local maximizers in mixture modeling
This page was built for publication: The Mixturegram: A Visualization Tool for Assessing the Number of Components in Finite Mixture Models