S3 methods for PRIM for multivariate data

S3 methods PRIM for multivariate data.

Usage

# S3 method for class 'prim'
predict(object, newdata, y.fun.flag=FALSE, ...)
# S3 method for class 'prim'
summary(object, ..., print.box=FALSE)

Arguments

object: object of class prim
newdata: data matrix
y.fun.flag: flag to return y value of PRIM box rather than box label. Default is FALSE.
print.box: flag to print out limits of all PRIM boxes. Default is FALSE.
...: other parameters

Details

–The predict method returns the value of PRIM box number in which newdata are located.

–The summary method displays a table with three columns: box-fun is the y value, box-mass is the mass of the box, threshold.type is the threshold direction indicator: 1 = ">= threshold", -1 = "<=threshold". Each box corresponds to a row. The second last row marked with an asterisk is the box which collates the remaining data points not belonging to a specific PRIM box. The final row is an overall summary, i.e. box-fun is the overall mean of y and box-mass is 1.

Examples

data(quasiflow)
qf <- quasiflow[1:1000,1:2]
qf.label <- quasiflow[1:1000,3]*quasiflow[1:1000,4]

qf.prim <- prim.box(x=qf, y=qf.label, threshold=c(0.3, -0.1), threshold.type=0)
summary(qf.prim)
#>             box-fun box-mass threshold.type
#> box1     0.39975894    0.131              1
#> box2     0.17537930    0.109              1
#> box3     0.38370978    0.052              1
#> box4    -0.13063967    0.087             -1
#> box5*   -0.01793194    0.621             NA
#> overall  0.06893629    1.000             NA
#> 
predict(qf.prim, newdata=c(0.6,0.2))
#> [1] 2

## using median insted of mean for the response y
qf.prim2 <- prim.box(x=qf, y=qf.label, threshold=c(0.5, -0.2),
  threshold.type=0, y.fun=median)
summary(qf.prim2)
#>            box-fun box-mass threshold.type
#> box1     0.8504155    0.144              1
#> box2    -0.2216066    0.233             -1
#> box3*    0.1634349    0.623             NA
#> overall  0.1726454    1.000             NA
#> 
predict(qf.prim2, newdata=c(0.6,0.2))
#> [1] 3