DescTools (version 0.99.19)

PairApply: Pairwise Calculations

Description

Implements a logic to run pairwise calculations on the columns of a data.frame or a matrix.

Usage

PairApply(x, FUN = NULL, ..., symmetric = FALSE)

Arguments

x

a list, a data.frame or a matrix with columns to be processed pairwise.

FUN

a function to be calculated. It is assumed, that the first 2 arguments denominate x and y.

...

the dots are passed to FUN.

symmetric

logical. Does the function yield the same result for FUN(x, y) and FUN(y, x)? If TRUE just the lower triangular matrix is calculated and transposed. Default is FALSE.

Value

Details

This code is based on the logic of cor() and extended for asymmetric functions.

See Also

outer, CombPairs, pairwise.table

Examples

PairApply(d.diamonds[,c("colour","clarity","cut","polish")], FUN = CramerV, 
          symmetric=TRUE)

# user defined functions are ok as well
PairApply(d.diamonds[,c("clarity","cut","polish","symmetry")], 
  FUN = function(x,y) wilcox.test(as.numeric(x), as.numeric(y))$p.value, symmetric=TRUE)

# asymetric measure
PairApply(d.diamonds[,c("colour", "clarity", "cut", "polish")], 
  FUN = Lambda, direction = "row")

# ... compare to:
Lambda(x=d.diamonds$colour, y=d.diamonds$clarity, direction="row")  
Lambda(x=d.diamonds$colour, y=d.diamonds$clarity, direction="column")  


# the data.frame
dfrm <- d.diamonds[, c("colour","clarity","cut","polish")]
PairApply(dfrm, FUN = CramerV, symmetric=TRUE)

# the same as matrix (columnwise)
m <- as.matrix(dfrm)
PairApply(m, FUN = CramerV, symmetric=TRUE)

# ... and the list interface
lst <- as.list(dfrm)
PairApply(lst, FUN = CramerV, symmetric=TRUE)