R: Allows to transform a continuous variable into a categorical...
var.bin
R Documentation
Allows to transform a continuous variable into a categorical ordinal one
by applying a modified version of the k-means clustering function in the 'stats' package.
Description
The optimization of a frame stratification is applicable only in presence of all categorical
auxiliary variables in the frame. If one or more continuous auxiliary variables are in the frame,
it is necessary to pre-process in order to convert them into categorical (ordinal) variables.
The applied method is the "k-means" clustering method contained in the in "stats" package.
This function ensures that the final result is in an ordered categorical variable.
Usage
var.bin(x,
bins=3,
iter.max=100)
Arguments
x
Continuous variable to be transformed into a categorical one
bins
Number of values of the resulting categorical variable
iter.max
Maximum number of iterations of the clustering algorithm
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.
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'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(SamplingStrata)
Loading required package: memoise
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/SamplingStrata/var.bin.Rd_%03d_medium.png", width=480, height=480)
> ### Name: var.bin
> ### Title: Allows to transform a continuous variable into a categorical
> ### ordinal one by applying a modified version of the k-means clustering
> ### function in the 'stats' package.
> ### Aliases: var.bin
> ### Keywords: survey
>
> ### ** Examples
>
> ## No test:
> library(SamplingStrata)
> data(swissmunicipalities)
> data(swissframe)
> swissframe$X1 <- var.bin(swissmunicipalities$POPTOT,bins = 18)
> table(swissframe$X1)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
774 554 374 308 234 180 123 96 58 55 49 30 32 13 8 3 4 1
> tapply(swissmunicipalities$POPTOT,swissframe$X1,mean)
1 2 3 4 5 6
195.9845 534.9928 947.1310 1436.1331 2106.8291 2936.9667
7 8 9 10 11 12
3918.9756 5010.8229 6308.8276 7881.3818 10244.9184 13467.1333
13 14 15 16 17 18
17059.0625 24961.6923 37363.5000 74201.6667 149517.5000 363273.0000
> ## End(No test)
>
>
>
>
>
> dev.off()
null device
1
>