Internal function: computes variance of compositional data set with missing/zero values
Computes an unbiased estimate of the variance of a compositional data set with some missing and zero values.
gsi.varwithlosts(x,giveCenter=FALSE)
x |
data set of the classes in |
giveCenter |
a logical. If TRUE the function reports the mean as an attribute "center" to the result. |
Do not use gsi.* functions directly since they are internal functions of the package.
R. Tolosana-Delgado, K.Gerald v.d. Boogaart http://www.stat.boogaart.de
van den Boogaart, K. G., R. Tolosana-Delgado, and M. Bren (2006) Concepts for handling of zeros and missing values in compositional data, In: 2006 Annual Conference of the International Association for Mathematical Geology (IAMG), Universit\'e de Li\'ege, Belgium.
Bren, M., R. Tolosana-Delgado, and K.G. van den Boogaart (2008) News
from compositions, the R package. In: Daunis-i-Estadella, J. and
Mart\'in-Fern\'a ndez, J.A. (Eds.)
Proceedings of the 3rd International Workshop on Compositional Data Analysis,
Universitat de Girona, Spain. http://ima.udg.es/Activitats/CoDaWork03/
# generates a 3-part compositional data set with missings
A <- matrix(c(0.5,0.3,0.1, 0.3,0.2,0, 0.1, 0, 0.75),nrow=3)
Mvar <- 2*ilrvar2clr(A)
Mcenter <- acomp(c(1,5,2,3))
x <- rnorm.acomp(100,Mcenter,Mvar)
colnames(x)<-c("A","B","C","D")
# eliminate 20 values completely at random
slost <- sample(1:length(x), size=30)
x[slost] <- 0
# compute the variance with losts
#print(vr <- gsi.varwithlosts(cdt(x)))
# compare with MvarPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.