build: Building an EMM using New Data

In rEMM: Extensible Markov Model for Modelling Temporal Relationships Between Clusters

Building an EMM using New Data

Description

Add new data to an EMM.

Usage

build(x, newdata, ...)

Arguments

x	an EMM object. Note that the function will change the original EMM!
newdata	a vector (one observation), or a matrix or data.frame (each row is an observation)
...	further arguments. If newdata is a matrix or a data.frame then verbose = TRUE can be used to monitor the progress of building the model.

Details

build() performs clustering and also updates the TRACDS temporal layer.

NAs are handled in the data by using only the other dimensions if the data for dissimilarity computation (see package proxy).

Value

A reference to the changed EMM object with the data added. Note: EMM objects store all variable data in an environment which enables us to update partial data without copying the whole object. Assignment will not create a copy! Use the provided method copy().

See Also

Class TRACDS, fade and dist in proxy.

Examples

## load EMMTraffic data
data("EMMTraffic")
EMMTraffic

## create EMM
emm <- EMM(measure="eJaccard", threshold=0.2)

## build model using EMMTraffic data (note that the EMM object is
## changed without assignment!)
build(emm, EMMTraffic)
## same as: emm <- build(emm, EMMTraffic)

size(emm)
plot(emm)

## emm2 <- emm does not create a copy (just a reference)
## a "deep" copy is created using copy()
emm2<- copy(emm)

## convert the emm into a graph
as.igraph(emm)

rEMM documentation built on May 29, 2024, 4:35 a.m.