pmclust (version 0.2-1)

Set Global Variables: Set Global Variables According to the global matrix X.gbd (X.spmd)

Description

This function will set several sets of variables globally in the environment .pmclustEnv according to the global matrix X.gbd/X.spmd.

Usage

set.global.gbd(K = 2, X.gbd = NULL, PARAM = NULL,
      algorithm = c("em", "aecm", "apecm", "apecma", "kmeans"),
      RndEM.iter = 10)
  set.global(K = 2, X.spmd = NULL, PARAM = NULL,
      algorithm = c("em", "aecm", "apecm", "apecma", "kmeans"),
      RndEM.iter = 10)

Arguments

K

an original set of parameters generated by set.global.

X.gbd

an input GBD matrix.

X.spmd

an input SPMD matrix.

PARAM

an original set of parameters generated by set.global.

algorithm

an original set of parameters generated by set.global.

RndEM.iter

number of RndEM iterations.

Value

A new set of PARAM will be returned and several global variables will be set according to the data X.gbd/X.spmd.

Sets of global variables are store in the default environment .pmclustEnv.

Use readme to see all global variables set by this function.

Details

WARNING: A global variable named X.gbd/X.spmd should be set before calling set.global where X.gbd/X.spmd is a matrix containing data with dimension N.spmd * p. i.e. N.spmd observations and p variables.

X.gbd/X.spmd is supposed to exist in .GlobalEnv. If not, they should be as an input object and will be copied into .pmclustEnv which is less efficient.

References

Programming with Big Data in R Website: https://pbdr.org/

See Also

em.step, aecm.step, apecm.step, apecma.step.

Examples

# NOT RUN {
# Examples can be found in the help pages of em.step(),
# aecm.step(), apecm.step(), apecma.step(), and kmeans.step().
# }