vignettes/GRA.md

In Nisus-Liu/GRA: Grey Relational Analysis(GRA)

Grey Relational Analysis(GRA)

Grey Relational Analysis include two important function. First function: grey relational degree, which is similar to orrelation coefficient, if you want to evaluate some units, please transpose data frame before using this function. Second funtion: grey clustering, like hierarchical clustering, see hclust.

Grey Relational Degree

There are two usage of grey relational degree. This algorithm is to measure similarity of two variables, just like cor. You can transpose your data set if you want to evaluate some units.

• One is to inspect correlation of two variables, data type like:

| reference | v1 | v2 | v3 | |-----------|----|----|----| | 1.2 | 1.8|0.9 | 8.4| | 0.11 | 0.3|0.5 | 0.2| | 1.3 | 0.7|0.12|0.98| | 1.9 |1.09|2.8 |0.99|

reference: reference variable, grey relational degree between reference and v1... approximately measures the similarity of reference and v1.

• Another is to evaluate good or bad about some units.

| units | v1 | v2 | v3 | |-----------|----|----|----| | jiangsu | 1.8|0.9 | 8.4| | zhejiang | 0.3|0.5 | 0.2| | anhui | 0.7|0.12|0.98| | fujian |1.09|2.8 |0.99|

Example

## generate data
refer = c(1,1,1,1)
liaoning = c(0.064, 0.082,0.978,0.423)
shandong = c(0.101,0.3,1,0.917)
jiangsu = c(0.114,0.14,0.943, 0.315)
zhejiang = c(0.102,0.147,0.934,0.395)
fujian = c(0.022,0.053,0.927,0.061)
guangdong = c(1,1,0.012,1)
economyCompare = data.frame(refer, liaoning, shandong, jiangsu, zhejiang, fujian, guangdong)
rownames(economyCompare) = c("indGV", "indVA", "profit", "incomeTax")

## Grey Relational Degree
greyRelDegree = GRA(economyCompare)
greyRelDegree

Grey Clustering

Example

## Grey Clustering
GRA(economyCompare, cluster = T)

Nisus-Liu/GRA documentation built on May 3, 2019, 5:03 p.m.