Chernoff Faces

faces represent the rows of a data matrix by faces

faces(xy, which.row, fill = FALSE, nrow, ncol, scale = TRUE, byrow = FALSE, main, labels)

Arguments

xy

xy data matrix, rows represent individuals and columns attributes

which.row

defines a permutation of the rows of the input matrix

fill

if(fill==TRUE), only the first nc attributes of the faces are transformed, nc is the number of columns of xy

nrow

number of columns of faces on graphics device

ncol

number of rows of faces

scale

if(scale==TRUE), attributes will be normalized

byrow

if(byrow==TRUE), xy will be transposed

main

title

labels

character strings to use as names for the faces

Details

The features paramters of this implementation are: 1-height of face, 2-width of face, 3-shape of face, 4-height of mouth, 5-width of mouth, 6-curve of smile, 7-height of eyes, 8-width of eyes, 9-height of hair, 10-width of hair, 11-styling of hair, 12-height of nose, 13-width of nose, 14-width of ears, 15-height of ears. For details look at the literate program of faces

Value

a plot of faces is created on the graphics device, no numerical results

References

Chernoff, H. (1973): The use of faces to represent statistiscal assoziation, JASA, 68, pp 361–368. The smooth curves are computed by an algorithm found in Ralston, A. and Rabinowitz, P. (1985): A first course in numerical analysis, McGraw-Hill, pp 76ff. http://www.uni-bielefeld.de/fakultaeten/wirtschaftswissenschaften : S/R - functions : faces

Author

H. P. Wolf

Note

version 12/2003

See also

—

Examples

faces(rbind(1:3,5:3,3:5,5:7))


data(longley)
faces(longley[1:9,])


set.seed(17)
faces(matrix(sample(1:1000,128,),16,8),main="random faces")


if(interactive()){
  tke1 <- rep( list(list('slider',from=0,to=1,init=0.5,resolution=0.1)), 15)
  names(tke1) <- c('FaceHeight','FaceWidth','FaceShape','MouthHeight',
  'MouthWidth','SmileCurve','EyesHeight','EyesWidth','HairHeight',
  'HairWidth','HairStyle','NoseHeight','NoseWidth','EarWidth','EarHeight')
  tkfun1 <- function(...){
  tmpmat <- rbind(Min=0,Adjust=unlist(list(...)),Max=1)
  faces(tmpmat, scale=FALSE)
  }

  tkexamp( tkfun1, list(tke1), plotloc='left', hscale=2, vscale=2 )
}