# Generalized Network-Based Dimensionality Reduction and Analysis

## Documentation for package ‘nda’ version 0.1.13

- DESCRIPTION file.
- Package NEWS.

## Help Pages

nda-package | Package of Generalized Network-based Dimensionality Reduction and Analyses
biplot.nda | Biplot function for Generalized Network-based Dimensionality Reduction and Analysis (GNDA)
COVID19_2020 | Covid'19 case datesets of countries (2020), where the data frame has 138 observations of 18 variables.
CrimesUSA1990.X | Crimes in USA cities in 1990. Independent variables (X)
CrimesUSA1990.Y | Crimes in USA cities in 1990. Dependent variable (Y)
CWTS_2020 | CWTS Leiden's University Ranking 2020 for all scientific fields, within the period of 2016-2019. 1176 observations (i.e., universities), and 42 variables (i.e., indicators).
data_gen | Generate random block matrix for GNDA
dCor | Calculating distance correlation of two vectors or columns of a matrix
dCov | Calculating distance covariance of two vectors or columns of a matrix
fs.dimred | Feature selection for PCA, FA, and (G)NDA
fs.KMO | Feature selection for KMO
GOVDB2020 | Governmental and economic data of countries (2020), where the data frame has 138 observations of 2161 variables.
I40_2020 | NUTS2 regional development data (2020) of I4.0 readiness, where the data frame has 414 observations of 101 variables.
nda | Package of Generalized Network-based Dimensionality Reduction and Analyses
ndr | Genearlized Network-based Dimensionality Reduction and Analysis (GNDA)
normalize | Min-max normalization
pdCor | Calculating partial distance correlation of columns of a matrix
plot.nda | Plot function for Generalized Network-based Dimensionality Reduction and Analysis (GNDA)
spdCor | Calculating semi-partial distance correlation of columns of a matrix
summary.nda | Summary function of Generalized Network-based Dimensionality Reduction and Analysis (GNDA)