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

data_gen | R Documentation |

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

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

`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 |

`n`

, `m`

, `nfactors`

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

`M` |
a dataframe of a block matrix |

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

```
# 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))
```

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