Package: rEMM 1.2.1
rEMM: Extensible Markov Model for Modelling Temporal Relationships Between Clusters
Implements TRACDS (Temporal Relationships between Clusters for Data Streams), a generalization of Extensible Markov Model (EMM). TRACDS adds a temporal or order model to data stream clustering by superimposing a dynamically adapting Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN data stream clustering). Development of this package was supported in part by NSF IIS-0948893 and R21HG005912 from the National Human Genome Research Institute. Hahsler and Dunham (2010) <doi:10.18637/jss.v035.i05>.
Authors:
rEMM_1.2.1.tar.gz
rEMM_1.2.1.zip(r-4.5)rEMM_1.2.1.zip(r-4.4)rEMM_1.2.1.zip(r-4.3)
rEMM_1.2.1.tgz(r-4.4-any)rEMM_1.2.1.tgz(r-4.3-any)
rEMM_1.2.1.tar.gz(r-4.5-noble)rEMM_1.2.1.tar.gz(r-4.4-noble)
rEMM_1.2.1.tgz(r-4.4-emscripten)rEMM_1.2.1.tgz(r-4.3-emscripten)
rEMM.pdf |rEMM.html✨
rEMM/json (API)
NEWS
# Install 'rEMM' in R: |
install.packages('rEMM', repos = c('https://mhahsler.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mhahsler/remm/issues
- Alphaproteobacteria16S - Count Data for 16S rRNA Sequences
- Derwent - Derwent Catchment Data
- EMMTraffic - Hypothetical Traffic Data Set for EMM
- EMMsim_sequence_test - Synthetic Data to Demonstrate EMMs
- EMMsim_sequence_train - Synthetic Data to Demonstrate EMMs
- EMMsim_test - Synthetic Data to Demonstrate EMMs
- EMMsim_train - Synthetic Data to Demonstrate EMMs
- Mollicutes16S - Count Data for 16S rRNA Sequences
clusteringdata-streamsequence-analysis
Last updated 3 months agofrom:a9c599d472. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 26 2024 |
R-4.5-win | OK | Oct 26 2024 |
R-4.5-linux | OK | Oct 26 2024 |
R-4.4-win | OK | Oct 26 2024 |
R-4.4-mac | OK | Oct 26 2024 |
R-4.3-win | OK | Oct 26 2024 |
R-4.3-mac | OK | Oct 26 2024 |
Exports:as.graphas.graph.TRACDSas.igraphas.igraph.TRACDSbuildclustercluster_centerscluster_countsclusterscompactcopycurrent_stateDSC_EMMDSC_tNNEMMfadefind_clustersget_EMMinitial_transitionlast_clusteringmerge_clustersnclustersnstatesntransitionsobject.sizeplotpredictprunerare_clustersrare_transitionsrecluster_hclustrecluster_kmeansrecluster_pamrecluster_reachabilityrecluster_tNNrecluster_transitionsremove_clustersremove_selftransitionsremove_transitionsresetscoreset_EMMsizesmooth_transitionsstatessynthetic_streamtNNTRACTRACDStransitiontransition_matrixtransition_tabletransitionsupdate
Dependencies:BHclasscliclueclusterclusterGenerationcpp11dbscanDEoptimRdiptestflexmixfpcgenericsglueigraphkernlablatticelifecyclemagrittrMASSMatrixmclustmlbenchmodeltoolsnnetpkgconfigprabclusproxyRcpprlangrobustbaserpartstreamvctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Count Data for 16S rRNA Sequences | 16S Alphaproteobacteria16S Mollicutes16S |
Building an EMM using New Data | build build,EMM,data.frame-method build,EMM,matrix-method build,EMM,numeric-method |
Data stream clustering with tNN | cluster cluster,tNN,data.frame-method cluster,tNN,matrix-method cluster,tNN,numeric-method |
Combining EMM Objects | c c,EMM-method |
Derwent Catchment Data | Derwent |
DSC Interface for EMM and tNN (package stream) | DSC_EMM DSC_tNN get_EMM set_EMM |
Creator for Class "EMM" | EMM object.size,EMM-method |
Class "EMM" | copy copy,EMM-method EMM-class show,EMM-method size size,EMM-method |
Synthetic Data to Demonstrate EMMs | EMMsim EMMsim_sequence_test EMMsim_sequence_train EMMsim_test EMMsim_train |
Hypothetical Traffic Data Set for EMM | EMMTraffic |
Fading Cluster Structure and EMM Layer | fade fade,EMM,missing,missing-method fade,EMM,missing,numeric-method fade,EMM,numeric,missing-method fade,EMM,numeric,numeric-method |
Find the EMM State/Cluster for an Observation | find_clusters find_clusters,tNN,data.frame-method find_clusters,tNN,matrix-method find_clusters,tNN,numeric-method |
Merge States of an EMM | merge_clusters merge_clusters,EMM,character-method merge_clusters,EMM,integer-method |
Visualize EMM Objects | plot plot,EMM,missing-method |
Predict a Future State | predict predict,TRACDS-method |
Prune States and/or Transitions | prune prune,EMM-method rare_clusters rare_clusters,tNN-method rare_transitions rare_transitions,TRACDS-method |
Reclustering EMM states | recluster recluster_hclust recluster_hclust,EMM-method recluster_kmeans recluster_kmeans,EMM-method recluster_pam recluster_pam,EMM-method recluster_reachability recluster_reachability,EMM-method recluster_tNN recluster_tNN,EMM-method recluster_transitions recluster_transitions,EMM-method |
Remove States/Clusters or Transitions from an EMM | remove_clusters remove_clusters,EMM,character-method remove_selftransitions remove_selftransitions,EMM-method remove_transitions remove_transitions,EMM,character,character-method remove_transitions,EMM,matrix,missing-method |
Score a New Sequence Given an EMM | score score,EMM,data.frame-method score,EMM,EMM-method score,EMM,matrix-method score,EMM,numeric-method |
Smooths transition counts between neighboring states/clusters | smooth_transitions smooth_transitions,EMM-method |
Create a Synthetic Data Stream | synthetic_stream |
Class "tNN" | clusters clusters,tNN-method cluster_centers cluster_centers,tNN-method cluster_counts cluster_counts,tNN-method copy,tNN-method last_clustering last_clustering,tNN-method nclusters nclusters,tNN-method object.size,tNN-method plot,tNN,missing-method StreamClustering-class tNN tNN-class |
TRAC: Creating a Markov Model from a Regular Clustering | TRAC |
Class "TRACDS" | as.graph as.graph.TRACDS as.igraph as.igraph.TRACDS copy,TRACDS-method current_state current_state,TRACDS-method nstates nstates,TRACDS-method ntransitions ntransitions,TRACDS-method object.size,TRACDS-method plot,TRACDS,missing-method show,TRACDS-method states states,TRACDS-method TRACDS TRACDS-class transitions transitions,TRACDS-method |
Access Transition Probabilities/Counts in an EMM | initial_transition initial_transition,TRACDS-method transition transition,TRACDS,character,character-method transition,TRACDS,data.frame,missing-method transition,TRACDS,matrix,missing-method transition_matrix transition_matrix,TRACDS-method |
Extract a Transition Table for a New Sequence Given an EMM | transition_table transition_table,EMM,data.frame-method transition_table,EMM,matrix-method transition_table,EMM,numeric-method |
Update a TRACDS temporal structure with new state assignements | compact compact,TRACDS-method reset reset,TRACDS-method update update,TRACDS-method |