qbpca {bpca} | R Documentation |
This function returns an object of the class qbpca
. It is a simple
measure of the quality of biplot representation of the variables. The
observed (in the data) and projected (under biplot reduction) correlations
are computed.
qbpca(x, bpca)
x |
A data.frame or matrix object. |
bpca |
A object of the class bpca . |
This function binds the vectors of observed (from the matrix or data.frame) and projected (under biplot reduction) correlations for all variables.
An object of class qbpca and data.frame with two columns:
obs |
A vector of the observed correlations for all variables. |
var.rb |
A vector of the projected correlations for all variables determined under biplot reduction). |
Jose Claudio Faria (joseclaudio.faria@gmail.com)
and
Clarice Garcia Borges Demetrio (clarice@esalq.usp.br)
Johnson, R. A. and Wichern, D. W. (1988) Applied multivariate statistical analysis. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 6 ed.
## ## Example 1 ## Example of 'var.rb=TRUE' parameter as a measure of the quality of the biplot - 2d ## library(bpca) ## Differences between methods of factorization # SQRT bp1 <- bpca(gabriel1971, meth='sqrt', var.rb=TRUE) qbp1 <- qbpca(gabriel1971, bp1) plot(qbp1, main='sqrt - 2d \n (poor)') # JK bp2 <- bpca(gabriel1971, meth='jk', var.rb=TRUE) qbp2 <- qbpca(gabriel1971, bp2) plot(qbp2, main='jk - 2d \n (very poor)') # GH bp3 <- bpca(gabriel1971, meth='gh', var.rb=TRUE) qbp3 <- qbpca(gabriel1971, bp3) plot(qbp3, main='gh - 2d \n (good)') # HJ bp4 <- bpca(gabriel1971, meth='hj', lambda.end=2, var.rb=TRUE) qbp4 <- qbpca(gabriel1971, bp4) plot(qbp4, main='hj - 2d \n (good)') ## ## Example 2 ## Example of 'var.rb=TRUE' parameter as a measure of the quality of the biplot - 3d ## library(bpca) ## Differences between methods of factorization # SQRT bp1 <- bpca(gabriel1971, meth='sqrt', lambda.end=3, var.rb=TRUE) qbp1 <- qbpca(gabriel1971, bp1) plot(qbp1, main='sqrt - 3d \n (poor)') # JK bp2 <- bpca(gabriel1971, meth='jk', lambda.end=3, var.rb=TRUE) qbp2 <- qbpca(gabriel1971, bp2) plot(qbp2, main='jk - 3d \n (very poor)') # GH bp3 <- bpca(gabriel1971, meth='gh', lambda.end=3, var.rb=TRUE) qbp3 <- qbpca(gabriel1971, bp3) plot(qbp3, main='gh - 3d \n (whow!)') # HJ bp4 <- bpca(gabriel1971, meth='hj', lambda.end=3, var.rb=TRUE) qbp4 <- qbpca(gabriel1971, bp4) plot(qbp4, main='hj - 3d \n (whow!)')