View source: R/interpret.dstatis.R
interpret.dstatis | R Documentation |
dstatis
function vs. moments of the densities
Applies to an object of class "dstatis"
, plots the principal scores vs. the moments of the densities (means, standard deviations, variances, correlations, skewness and kurtosis coefficients), and computes the correlations between these scores and moments.
## S3 method for class 'dstatis'
interpret(x, nscore = 1, moment=c("mean", "sd", "var", "cov", "cor",
"skewness", "kurtosis"), ...)
x |
object of class |
nscore |
numeric. Selects the column of the data frame Note that since dad-4, Warning: |
moment |
characters string. Selects the moments to cross with scores:
|
... |
Arguments to be passed to methods. |
A graphics device can contain up to 9 graphs. If there are too many (more than 36) graphs for each score, one can display the graphs in a multipage PDF file.
The number of principal scores to be interpreted cannot be greater than nb.factors
of the data frame x$scores
returned by the function dstatis.inter.
Returns a list including:
pearson |
matrix of Pearson correlations between selected scores and moments. |
spearman |
matrix of Spearman correlations between selected scores and moments. |
Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Gilles Hunault, Sabine Demotes-Mainard
Lavit, C., Escoufier, Y., Sabatier, R., Traissac, P. (1994). The ACT (STATIS method). Computational Statistics & Data Analysis, 18 (1994), 97-119.
dstatis.inter; plot.dstatis.
data(roses)
rosesf <- as.folder(roses[,c("Sha","Den","Sym","rose")])
# Dual STATIS on the covariance matrices
## Not run:
result <- dstatis.inter(rosesf, group.name = "rose")
interpret(result)
interpret(result, moment = "var")
interpret(result, moment = "cor")
interpret(result, nscore = 2)
## End(Not run)
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