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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