mkIndiList: Converts Data Frame to Indicator Matrix

Description Usage Arguments Details See Also Examples

View source: R/mkIndiList.R

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

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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

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## 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 May 30, 2017, 12:36 a.m.