Compare matrices using PCA similarity factor

Compare matrices using PCA similarity factor

pcasf(x, y, dim = NULL)

Arguments

x

Matrix with sample in column and features in row

y

Matrix is compared to x.

dim

number of retained dimensions in the comparison. Defaults to all.

Value

Ratio of projected variance to total variance

References

Singhal, A. and Seborg, D. E. (2005), Clustering multivariate time-series data. J. Chemometrics, 19: 427-438. doi: 10.1002/cem.945

Author

Edgar Zanella Alvarenga

Examples

c1 <- matrix(rnorm(16),nrow=4)
c2 <- matrix(rnorm(16),nrow=4)
pcasf(c1, c2)
#>     pcasf 
#> 0.5300772