Package: tip 0.1.0
Charles W. Harrison
tip: Bayesian Clustering Using the Table Invitation Prior (TIP)
Cluster data without specifying the number of clusters using the Table Invitation Prior (TIP) introduced in the paper "Clustering Gene Expression Using the Table Invitation Prior" by Charles W. Harrison, Qing He, and Hsin-Hsiung Huang (2022) <doi:10.3390/genes13112036>. TIP is a Bayesian prior that uses pairwise distance and similarity information to cluster vectors, matrices, or tensors.
Authors:
tip_0.1.0.tar.gz
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tip.pdf |tip.html✨
tip/json (API)
| # Install 'tip' in R: |
| install.packages('tip', repos = c('https://charleswharrison.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/charleswharrison/tip/issues
Last updated 5 months agofrom:fe35a3b7ad. Checks:3 OK, 6 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Apr 02 2025 |
| R-4.5-win | NOTE | Apr 02 2025 |
| R-4.5-mac | NOTE | Apr 02 2025 |
| R-4.5-linux | NOTE | Apr 02 2025 |
| R-4.4-win | NOTE | Apr 02 2025 |
| R-4.4-mac | NOTE | Apr 02 2025 |
| R-4.4-linux | NOTE | Apr 02 2025 |
| R-4.3-win | OK | Apr 02 2025 |
| R-4.3-mac | OK | Apr 02 2025 |
Exports:get_cpt_neighborsggnet2_network_plotggplot_line_pointggplot_number_of_clusters_histggplot_number_of_clusters_tracepartition_undirected_graphplottip
Dependencies:changepointclicodacodetoolscolorspacecpp11crayondoParalleldplyrfansifarverforcatsforeachgenericsGGallyggplot2ggstatsgluegtablehmsigraphisobanditeratorslabelingLaplacesDemonlatticelifecyclemagrittrMASSMatrixmgcvmniwmunsellnetworknlmepatchworkpillarpkgconfigplyrprettyunitsprogresspurrrR6RColorBrewerRcppRcppEigenrlangscalesstatnet.commonstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrzoo
iris-NIW-vignette
Rendered fromvector-NIW-iris-vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2022-11-09
Started: 2022-10-23
matrix-clustering-CONSTANT-vignette
Rendered frommatrix-CONSTANT-simulated-vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2022-11-09
Started: 2022-10-23
matrix-clustering-MNIW-vignette
Rendered frommatrix-MNIW-simulated-vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2022-11-09
Started: 2022-10-23
tensor-clustering-CONSTANT-vignette
Rendered fromtensor-CONSTANT-simulated-vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2022-11-09
Started: 2022-10-23
usarrests-NIW-vignette
Rendered fromvector-NIW-usarrests-vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2022-11-09
Started: 2022-10-23
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Clustering Model (bcm) S4 class. | bcm-class |
| Estimate the number of similar subjects | get_cpt_neighbors |
| Visualize the posterior similarity matrix (i.e., posterior probability matrix) | ggnet2_network_plot |
| Plot connected points using ggplot2 | ggplot_line_point |
| Plot the posterior distribution of the number of clusters. | ggplot_number_of_clusters_hist |
| Plot the trace plot of the posterior number of clusters | ggplot_number_of_clusters_trace |
| Partition an undirected graph | partition_undirected_graph |
| Generate plots from a Bayesian Clustering Model (bcm) object | plot plot,bcm,missing-method |
| Bayesian Clustering with the Table Invitation Prior | tip |