rg.mvalloc: Robust Multivariate Allocation Procedure

Description Usage Arguments Details Value Author(s) References Examples

Description

Function to allocate an individual to one of several populations.

Usage

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rg.mvalloc(pcrit = 0.05, x, ...)

Arguments

pcrit

When the probability of group membership is less than pcrit it is allocated to group 0.

x

contains the individuals to be allocated

...

arguments for creating a list of groups

Details

m objects are the reference populations generated by md.gait, rg.robmva or rg.mva to estimate Mahalanobis distancesand predicted probabilities of group membership for individuals in matrix x. Note that the log |determinant| of the appropriate covariance matrix is added to the Mahalanobis distance on the assumption that the covariance matrices are inhomogeneous. If the data require transformation this must be undertaken before calling this function. This implies that a similar transformation must have been used for all the reference data subsets.

Value

groups

the groups

m

number of groups

n

number of individuals to be allocated

p

number of columns

pgm

number of individuals to be allocated multiplied with the groups

pcrit

critical probability

xalloc

number of individuals as integer

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at> http://cstat.tuwien.ac.at/filz/

References

C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.

Examples

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#input data
data(ohorizon)
vegzn=ohorizon[,"VEG_ZONE"]
veg=rep(NA,nrow(ohorizon))
veg[vegzn=="BOREAL_FOREST"] <- 1
veg[vegzn=="FOREST_TUNDRA"] <- 2
veg[vegzn=="SHRUB_TUNDRA"] <- 3
veg[vegzn=="DWARF_SHRUB_TUNDRA"] <- 3
veg[vegzn=="TUNDRA"] <- 3
el=c("Ag","Al","As","B","Ba","Bi","Ca","Cd","Co","Cu","Fe","K","Mg","Mn",
  "Na","Ni","P","Pb","Rb","S","Sb","Sr","Th","Tl","V","Y","Zn")
x <- log10(ohorizon[!is.na(veg),el])
v <- veg[!is.na(veg)]

res.zone1=rg.mva(as.matrix(x[v==1,]))
res.zone2=rg.mva(as.matrix(x[v==2,]))
res.zone3=rg.mva(as.matrix(x[v==3,]))
res=rg.mvalloc(pcrit=0.01,x,res.zone1,res.zone2,res.zone3)

Example output

Loading required package: geoR
--------------------------------------------------------------
 Analysis of Geostatistical Data
 For an Introduction to geoR go to http://www.leg.ufpr.br/geoR
 geoR version 1.7-5.2.1 (built on 2016-05-02) is now loaded
--------------------------------------------------------------

Loading required package: sgeostat
Warning messages:
1: no DISPLAY variable so Tk is not available 
2: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
3: 'rgl_init' failed, running with rgl.useNULL = TRUE 
4: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
  n = 329 	nc = 329 	p = 27 		nc/p = 12.19 
  Eigenvalues: 7.39 3.37 3.227 2.465 1.751 1.597 1.045 0.8917 0.8494 0.5894 0.5627 0.4491 0.3906 0.3693 0.3042 0.2794 0.2435 0.2139 0.1794 0.1695 0.1453 0.1202 0.1078 0.08965 0.05534 0.04615 0.01626 
  n = 139 	nc = 139 	p = 27 		nc/p = 5.15 
  Eigenvalues: 7.999 4.196 2.843 2.498 2.079 1.183 1.06 0.773 0.6318 0.4884 0.478 0.4057 0.3643 0.2883 0.2668 0.2123 0.1734 0.1566 0.154 0.1309 0.109 0.08617 0.07937 0.05226 0.04218 0.03785 0.01623 
  n = 100 	nc = 100 	p = 27 		nc/p = 3.7 
  *** Proceed with Care, n is < 5p ***
  Eigenvalues: 8.369 3.73 2.54 2.092 1.764 1.58 1.446 0.775 0.733 0.6799 0.45 0.4143 0.3447 0.2657 0.2562 0.2183 0.2052 0.1669 0.1407 0.1192 0.1181 0.07443 0.0694 0.05564 0.04798 0.04274 0.03177 
  m = 3 	 px = 27 	 nx = 568 
  *** Proceed with Care, n < 5p for group as.matrix(x[v == 3, ]) ***

StatDA documentation built on March 13, 2020, 2:42 a.m.

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