Packaged: 2020-03-05 16:24:06 UTC; eriksaberski

Authors@R: c(person(given = "David", family = "Springate", role = "aut",
person(given = "Rosa", family = "Parisi", role = c("aut","cre"),
person(given = "Evangelos", family = "Kontopantelis", role = c("ctb"),
person(given = "Ivan", family = "Olier", role = c("ctb"),
Title: Manipulating and Analysing Electronic Health Record Data
Description: Tools for processing and extracting clinical information from
Depends: R (>= 3.0.2), sqldf, RSQLite, methods, utils, dplyr
Imports: assertthat, stringr, foreign, parallel, readstata13, combinat,
Suggests: testthat, devtools, roxygen2, knitr, reshape2, survival

Title: Extensible Markov Model (EMM) for Data Stream Clustering in R
Author: Michael Hahsler and Margaret H. Dunham
Description: The Extensible Markov Model (EMM) adds a temporal
component to data stream clustering by superimposing a
dynamically adapting Markov Chain. This package implements EMM
on top of threshold NN, a simple clustering algorithm for data
Depends: R (>= 2.7.0), methods, stats, graph, proxy, cluster, MASS,

streams. Development of this package was supported in part by
Depends: R (>= 2.7.0), methods, stats, proxy, cluster, MASS,

Title: Extensible Markov Model for Modelling Temporal Relationships
person("Margaret H.", "Dunham", role = c("aut", "cph")))
Description: 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.
Imports: methods, stats, clusterGeneration, MASS, utils

Imports: methods, stats, cluster, clusterGeneration, MASS, utils

Description: This package implements TRACDS (Temporal Relationships
between Clusters for Data Streams) which is 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. This package implements EMM (TRACDS on
top of tNN data stream clustering). Development of this package
was supported in part by NSF IIS-0948893.
Depends: R (>= 2.10.0), methods, stats, proxy, cluster, MASS,