Probabilistic clustering via Pareto solutions and significance tests
From MaRDI portal
Publication:2418354
DOI10.1007/s11634-016-0278-2zbMath1414.62243OpenAlexW2563646325MaRDI QIDQ2418354
María Teresa Gallegos, Gunter Ritter
Publication date: 3 June 2019
Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11634-016-0278-2
cluster analysismixture modelprobabilistic modelsBehrens-Fisher problemPareto solutionsHotelling's \(T^2\) statisticWilks' lambdaclassification model
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A fast algorithm for robust constrained clustering
- On mixtures of skew normal and skew \(t\)-distributions
- Strong consistency of \(k\)-parameters clustering
- Finite mixtures of multivariate skew \(t\)-distributions: some recent and new results
- On the Behrens-Fisher problem: a globally convergent algorithm and a finite-sample study of the Wald, LR and LM tests
- Using combinatorial optimization in model-based trimmed clustering with cardinality constraints
- Trimmed ML estimation of contaminated mixtures
- A constrained formulation of maximum-likelihood estimation for normal mixture distributions
- On some significance tests in cluster analysis
- Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
- MCLUST: Software for model-based cluster analysis
- Trimming algorithms for clustering contaminated grouped data and their robustness
- Finite mixture and Markov switching models.
- Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
- An Iterative Procedure for Obtaining Maximum-Likelihood Estimates of the Parameters for a Mixture of Normal Distributions
- Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model
- On the Identifiability of Finite Mixtures
- Estimating the components of a mixture of normal distributions
- The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses
- Numerical optimization. Theoretical and practical aspects. Transl. from the French
This page was built for publication: Probabilistic clustering via Pareto solutions and significance tests