rg.mva {StatDA}R Documentation

Non-robust Multivariate Data Analysis

Description

Procedure to undertake non-robust multivariate data analysis. The saved list may be passed to other rotation and display functions

Usage

rg.mva(x, main = deparse(substitute(x)))

Arguments

x data
main used for the list

Details

Procesure to undertake non-robust multivariate data analyses; the object generated is identical to that of rg.robmva so that the savedlist may be passed to other rotation and display functions. Thus weights are set to 1, and other variables are set to appropriate defaults. The estimation of Mahalanobis distances is only undertaken if x is nonsingular, i.e. the lowest eigenvalue is > 10e-4.

Value

n number of rows
p number of columns
wts the weights for the covariance matrix
mean the mean of the data
cov the covariance
sd the standard deviation
r correlation matrix
eigenvalues eigenvalues of the SVD
econtrib proportion of eigenvalues in %
eigenvectors eigenvectors of the SVD
rload loadings matrix
rcr standardised loadings matrix
vcontrib scores variance
pvcontrib proportion of scores variance in %
cpvcontrib cummulative proportion of scores variance
md Mahalanbois distance
ppm probability for outliegness using F-distribution
epm probability for outliegness using Chisquared-distribution

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at> http://www.statistik.tuwien.ac.at/public/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

#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)]

rg.mva(as.matrix(x[v==1,]))


[Package StatDA version 1.1 Index]