data_gen: Generate random block matrix for GNDA

View source: R/nda.R View source: R/data_gen.R

data_genR Documentation

Generate random block matrix for GNDA

Description

Generate random block matrix for Generalized Network-based Dimensionality Reduction and Analysis (GNDA)

Usage

data_gen(n,m,nfactors=2,lambda=1)

Arguments

n

number of rows

m

number of columns

nfactors

number of blocks (factors, where the default value is 2)

lambda

exponential smoothing, where the default value is 1

Details

n, m, nfactors must beintegers, and they are not less than 1; lambda should be a positive real number.

Value

M

a dataframe of a block matrix

Author(s)

Prof. Zsolt T. Kosztyan, Department of Quantitative Methods, Institute of Management, Faculty of Business and Economics, University of Pannonia, Hungary

e-mail: kzst@gtk.uni-pannon.hu

Examples

# Specification 30 by 10 random block matrices with 2 blocks/factors
df<-data_gen(30,10)
library(psych)
scree(df)
biplot(ndr(df))
# Specification 40 by 20 random block matrices with 3 blocks/factors
df<-data_gen(40,20,3)
library(psych)
scree(df)
biplot(ndr(df))
plot(ndr(df))

# Specification 50 by 20 random block matrices with 4 blocks/factors
# lambda=0.1
df<-data_gen(50,15,4,0.1)
scree(df)
biplot(ndr(df))
plot(ndr(df))

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