mkIndiList: Converts Data Frame to Indicator Matrix

In anacor: Simple and Canonical Correspondence Analysis

Converts Data Frame to Indicator Matrix

Description

This function takes a data frame, a vector of types, a list of knot vectors, and a vector of orders. It returns a list of codings for the variables, i.e., crisp indicator, numerical version, or fuzzy indicator.

Usage

mkIndiList(data, type = rep("C",dim(data)[2]), knots, ord)

Arguments

data	Data frame to be converted.
type	If "C", a crisp indicator is returned; if "A", a numerical version; if "F", the b-spline basis as a fuzzy indicator.
knots	List of knot sequences for type-F coding.
ord	Vector with b-spline order for type-F coding.

Details

For the fuzzy coding, the variable values need to be provided as integers. Each list element contains a vector with knots (breaks) for each variable separately. The order is defined through the ord argument as vector (again, for each variable). See bsplines help file for more details.

See Also

expandFrame, burtTable

Examples

## sleeping bags crisp and numeric
data(sleeping)
sleeping_cat <- sleeping
temp_cat <- cut(sleeping$Temperature, c(-20, -1, 7), labels = c("warm", "cold")) 
sleeping_cat$Temperature <- temp_cat
weight_cat <- cut(sleeping$Weight, c(700, 1100, 2200), labels = c("light", "heavy")) 
sleeping_cat$Weight <- weight_cat
price_cat <- cut(sleeping$Price, c(100, 250, 350, 700), 
labels = c("cheap", "medium", "expensive"))  
sleeping_cat$Price <- price_cat
sleeping_cat
mkIndiList(sleeping_cat)     ## crisp
mkIndiList(sleeping_cat, type = rep("A", ncol(sleeping_cat)))     ## numeric
mkIndiList(sleeping_cat, type = c("A","A","A","C"))     ## mixed

## artificial data fuzzy coding
x1 <- sample(1:6, 20, replace = TRUE) 
x2 <- sample(1:3, 20, replace = TRUE)
data <- data.frame(x1,x2)
knots <- list(c(1,3,5,6), c(1,2,3))
ord <- c(2,1)
mkIndiList(data, type = c("F","F"), knots = knots, ord = ord)

## Also mixed indicator versions are possible
mkIndiList(data, type = c("C","F"), knots = knots, ord = ord)

anacor documentation built on June 10, 2022, 5:09 p.m.