rg.mva: Non-robust Multivariate Data Analysis

In StatDA: Statistical Analysis for Environmental Data

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 <[e-mail]> 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

#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,]))

StatDA documentation built on June 7, 2023, 6:26 p.m.