Package: mixture 2.1.1
Paul D. McNicholas
mixture: Mixture Models for Clustering and Classification
An implementation of 14 parsimonious mixture models for model-based clustering or model-based classification. Gaussian, Student's t, generalized hyperbolic, variance-gamma or skew-t mixtures are available. All approaches work with missing data. Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>, Browne and McNicholas (2014) <doi:10.1007/s11634-013-0139-1>, Browne and McNicholas (2015) <doi:10.1002/cjs.11246>.
Authors:
mixture_2.1.1.tar.gz
mixture_2.1.1.tar.gz(r-4.5-noble)mixture_2.1.1.tar.gz(r-4.4-noble)
mixture_2.1.1.tgz(r-4.4-emscripten)mixture_2.1.1.tgz(r-4.3-emscripten)
mixture.pdf |mixture.html✨
mixture/json (API)
| # Install 'mixture' in R: |
| install.packages('mixture', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 months agofrom:e6f0d3e23a. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 27 2024 |
| R-4.5-linux-x86_64 | OK | Aug 27 2024 |
Exports:ARIe_stepget_best_modelghpcmgpcmmain_loopmain_loop_ghmain_loop_stmain_loop_tmain_loop_vgMAPpcmstpcmtpcmvgpcmz_ig_kmeansz_ig_random_hardz_ig_random_soft
Dependencies:BHlatticeRcppRcppArmadilloRcppGSL
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Adjusted Rand Index | ARI |
| Expectation Step | e_step |
| Best Model Extractor | get_best_model |
| Generalized Hyperbolic Parsimonious Clustering Models | ghpcm |
| Gaussian Parsimonious Clustering Models | gpcm |
| GPCM Internal C++ Call | main_loop |
| GHPCM Internal C++ Call | main_loop_gh |
| STPCM Internal C++ Call | main_loop_st |
| TPCM Internal C++ Call | main_loop_t |
| VGPCM Internal C++ Call | main_loop_vg |
| Maximum _a posterori_ | MAP |
| Mixture Models for Clustering and Classification | mixture-package mixture |
| Parsimonious Clustering Models | pcm |
| Skew-t Parsimonious Clustering Models | stpcm |
| Skewed Simulated Data 1 | sx2 |
| Skewed Simulated Data 2 | sx3 |
| Student T Parsimonious Clustering Models | tpcm |
| Variance Gamma Parsimonious Clustering Models | vgpcm |
| Simulated Data | x2 |
| K-means Initialization | z_ig_kmeans |
| Random Hard Initialization | z_ig_random_hard |
| Random Soft Initialization | z_ig_random_soft |