rEMM v1.0-11


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by Michael Hahsler

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.

Functions in rEMM

Name Description
find_clusters Find the EMM State/Cluster for an Observation
EMMTraffic Hypothetical Traffic Data Set for EMM
EMM Creator for Class "EMM"
predict Predict a Future State
EMM-class Class "EMM"
score Score a New Sequence Given an EMM
prune Prune States and/or Transitions
fade Fading Cluster Structure and EMM Layer
transition Access Transition Probabilities/Counts in an EMM
Derwent Derwent Catchment Data
build Building an EMM using New Data
remove Remove States/Clusters or Transitions from an EMM
tNN-class Class "tNN"
smooth_transitions Smooths transition counts between neighboring states/clusters
cluster Data stream clustering with tNN
merge_clusters Merge States of an EMM
16S Count Data for 16S rRNA Sequences
transition_table Extract a Transition Table for a New Sequence Given an EMM
recluster Reclustering EMM states
combine Combining EMM Objects
update Update a TRACDS temporal structure with new state assignements
EMMsim Synthetic Data to Demonstrate EMMs
TRACDS-class Class "TRACDS"
synthetic_stream Create a Synthetic Data Stream
plot Visualize EMM Objects
TRAC TRAC: Creating an EMM from a Regular Clustering
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Last month downloads


Date 2015-07-23
Classification/ACM G.4, H.2.8, I.5.1
License GPL-2
NeedsCompilation yes
Packaged 2015-07-23 22:02:39 UTC; hahsler
Repository CRAN
Date/Publication 2015-07-24 07:54:05

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