Printing results of a functional PCA of probability densities

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Description

Applies to an object of class "fpcad". Prints the numeric results returned by the fpcad function.

Usage

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## S3 method for class 'fpcad'
print(x, mean.print = FALSE, var.print = FALSE,
  cor.print = FALSE, skewness.print = FALSE, kurtosis.print = FALSE,
  digits = 2, ...)

Arguments

x

object of class "fpcad", returned by the fpcad function.

mean.print

logical. If TRUE, prints for each group the means and standard deviations of the variables and the norm of the density.

var.print

logical. If TRUE, prints for each group the variances and covariances of the variables.

cor.print

logical. If TRUE, prints for each group the correlations between the variables.

skewness.print

logical. If TRUE, prints for each group the skewness coefficients of the variables.

kurtosis.print

logical. If TRUE, prints for each group the kurtosis coefficients of the variables.

digits

numeric. Number of significant digits for the display of numeric results.

...

optional arguments to print methods.

Details

By default, are printed the inertia explained by the nb.values (see fpcad) first principal components, the contributions, the qualities of representation of the densities along the nb.factors (see fpcad) first principal components, and the principal scores.

Author(s)

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard.

References

Boumaza, R., Yousfi, S., Demotes-Mainard, S. (2015). Interpreting the principal component analysis of multivariate density functions. Communications in Statistics - Theory and Methods, 44 (16), 3321-3339.

See Also

fpcad; plot.fpcad; interpret.fpcad; print.

Examples

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data(roses)
result = fpcad(roses)
print(result)
print(result, mean.print=TRUE)

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