summary.nda: Summary function of Generalized Network-based Dimensionality...

View source: R/summary.nda.R View source: R/nda.R

summary.ndaR Documentation

Summary function of Generalized Network-based Dimensionality Reduction and Analysis (GNDA)

Description

Print summary of Generalized Network-based Dimensionality Reduction and Analysis (GNDA)

Usage

## S3 method for class 'nda'
summary(object, digits = getOption("digits"), ...)

Arguments

object

an object of class 'nda'.

digits

the number of significant digits to use when add.stats = TRUE.

...

additional arguments affecting the summary produced.

Value

communality

Communality estimates for each item. These are merely the sum of squared factor loadings for that item. It can be interpreted in correlation matrices.

loadings

A standard loading matrix of class “loadings".

uniqueness

Uniqueness values of indicators.

factors

Number of found factors.

scores

Estimates of the factor scores are reported (if covar=FALSE).

n.obs

Number of observations specified or found.

Author(s)

Zsolt T. Kosztyan*, Marcell T. Kurbucz, Attila I. Katona

e-mail*: kosztyan.zsolt@gtk.uni-pannon.hu

References

Kosztyán, Z. T., Katona, A. I., Kurbucz, M. T., & Lantos, Z. (2024). Generalized network-based dimensionality analysis. Expert Systems with Applications, 238, 121779. <URL: https://doi.org/10.1016/j.eswa.2023.121779>.

See Also

biplot, plot, print, ndr.

Examples

# Example of summary function of NDA without feature selection

data("CrimesUSA1990.X")
df<-CrimesUSA1990.X
p<-ndr(df)
summary(p)

# Example of summary function of NDA with feature selection
# minimal eigen values (min_evalue) is 0.0065
# minimal communality value (min_communality) is 0.1
# minimal common communality value (com_communalities) is 0.1

p<-ndr(df,min_evalue = 0.0065,min_communality = 0.1,com_communalities = 0.1)
summary(p)


kzst/nda documentation built on Nov. 30, 2024, 3:41 p.m.