R: General pourpose multivariate binary Clustering (EMbC)
embc
R Documentation
General pourpose multivariate binary Clustering (EMbC)
Description
embc implements the core function of the Expectation-Maximization multivariate binary clustering.
Usage
embc(X, U = NULL, stdv = NULL, maxItr = 200, info = 0)
Arguments
X
The input data set. A multivariate matrix where each row is a data point and each column is an input feature (a variable).
U
A multivariate matrix with same dimension as X with the values of certainty associated to each corresponding value in X. Ceartainties assign reliability to the data points so that the less reliable is a data point the less its leverage in the clustering. By default certainties are set to one (no uncertainty in any value in X).
stdv
a vector with bounds for the maximum precission of clusters, given as minimum standard deviation for each variable, (by default is set to rep(1e-30,ncol(X))
maxItr
A limit to the number of iterations in case of slow convergence (defaults to 200).
info
Level of information shown at each step:
info=0 (default) shows step likelihood, number of clusters, and number of changing labels;
info=1 includes clustering statistics;
info=2 includes delimiters information;
info<0 supresses any step information.
Value
Returns a binClst object.
Examples
# -- apply EMbC to the example set of data points x2d ---
mybc <- embc(x2d@D)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(EMbC)
Loading required package: move
Loading required package: geosphere
Loading required package: sp
Loading required package: raster
Loading required package: rgdal
rgdal: version: 1.1-10, (SVN revision 622)
Geospatial Data Abstraction Library extensions to R successfully loaded
Loaded GDAL runtime: GDAL 1.11.3, released 2015/09/16
Path to GDAL shared files: /usr/share/gdal/1.11
Loaded PROJ.4 runtime: Rel. 4.9.2, 08 September 2015, [PJ_VERSION: 492]
Path to PROJ.4 shared files: (autodetected)
Linking to sp version: 1.2-3
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EMbC/embc.Rd_%03d_medium.png", width=480, height=480)
> ### Name: embc
> ### Title: General pourpose multivariate binary Clustering (EMbC)
> ### Aliases: embc
>
> ### ** Examples
>
> # -- apply EMbC to the example set of data points x2d ---
> mybc <- embc(x2d@D)
... computing starting delimiters:
... delimiter Ll : 3.323976
... delimiter Lh : 3.323976
... delimiter Hl : 3.323976
... delimiter Hh : 3.323976
... delimiter lL : 6.355656
... delimiter hL : 6.355656
... delimiter lH : 4.780901
... delimiter hH : 4.780901
[1] 0 -0.0000e+00 4 400
[1] 1 -5.4865e+00 4 285
[1] 2 -5.3248e+00 4 15
[1] 3 -5.1641e+00 4 13
[1] 4 -5.0540e+00 4 9
[1] 5 -4.9903e+00 4 7
[1] 6 -4.9593e+00 4 9
[1] 7 -4.9446e+00 4 5
[1] 8 -4.9359e+00 4 5
[1] 9 -4.9306e+00 4 6
[1] 10 -4.9281e+00 4 3
[1] 11 -4.9270e+00 4 3
[1] 12 -4.9265e+00 4 3
[1] 13 -4.9270e+00 4 2
[1] 14 -4.9281e+00 4 4
[1] 15 -4.9282e+00 4 1
[1] 16 -4.9278e+00 4 4
[1] 17 -4.9279e+00 4 3
[1] 18 -4.9274e+00 4 4
[1] 19 -4.9300e+00 4 6
[1] 20 -4.9291e+00 4 3
[1] 21 -4.9292e+00 4 0
[1] 22 -4.9295e+00 4 0
[1] 23 -4.9293e+00 4 2
[1] 24 -4.9291e+00 4 0
[1] 25 -4.9288e+00 4 2
[1] 26 -4.9287e+00 4 1
[1] 27 -4.9293e+00 4 0
[1] 28 -4.9289e+00 4 2
[1] 29 -4.9296e+00 4 0
[1] 30 -4.9296e+00 4 0
[1] 31 -4.9294e+00 4 0
[1] 32 -4.9294e+00 4 0
[1] 33 -4.9294e+00 4 0
[1] ... Stable clustering
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> dev.off()
null device
1
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providing 
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