latrend: lcMethodRandom – R documentation

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lcMethodRandom

Specify a random-partitioning method

Description

Creates a model with random cluster assignments according to the random cluster proportions drawn from a Dirichlet distribution.

Usage

lcMethodRandom(
  response,
  alpha = 10,
  center = meanNA,
  time = getOption("latrend.time"),
  id = getOption("latrend.id"),
  nClusters = 2,
  name = "random"
)

Arguments

`response`	The name of the response variable.
`alpha`	The Dirichlet parameters. Either `scalar` or of length `nClusters`. The higher alpha, the more uniform the clusters will be.
`center`	Optional `function` for computing the longitudinal cluster centers, with signature `(x)`.
`time`	The name of the time variable.
`id`	The name of the trajectory identification variable.
`nClusters`	The number of clusters.
`name`	The name of the method.

References

Frigyik BA, Kapila A, Gupta MR (2010). “Introduction to the Dirichlet distribution and related processes.” Technical Report UWEETR-2010-0006, Department of Electrical Engineering, University of Washington.

Examples

data(latrendData)
method <- lcMethodRandom(response = "Y", id = "Id", time = "Time")
model <- latrend(method, latrendData)

# uniform clusters
method <- lcMethodRandom(alpha = 1e3, nClusters = 3, response = "Y", id = "Id", time = "Time")

# single large cluster
method <- lcMethodRandom(alpha = c(100, 1, 1, 1), nClusters = 4,
  response = "Y", id = "Id", time = "Time")

latrend

A Framework for Clustering Longitudinal Data

v1.1.2

GPL (>= 2)

Authors

Initial release

2021-04-14