Converts Data Frame to Indicator Matrix
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.
mkIndiList(data, type = rep("C",dim(data)[2]), knots, ord)
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.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.
expandFrame, burtTable
## 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)