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discrete.recode

Recodes mixed variables dataset


Description

Recodes a dataset with mixed continuous and categorical variables so that the continuous variables come first and the categorical variables have standard coding 1, 2, 3,... (in lexicographical ordering of values coerced to strings).

Usage

discrete.recode(x,xvarsorted=TRUE,continuous=0,discrete)

Arguments

x

data matrix or data frame. The data need to be organised case-wise, i.e., if there are categorical variables only, and 15 cases with values c(1,1,2) on the 3 variables, the data matrix needs 15 rows with values 1 1 2. (Categorical variables could take numbers or strings or anything that can be coerced to factor levels as values.)

xvarsorted

logical. If TRUE, the continuous variables are assumed to be the first ones, and the categorical variables to be behind them.

continuous

vector of integers giving positions of the continuous variables. If xvarsorted=TRUE, a single integer, number of continuous variables.

discrete

vector of integers giving positions of the categorical variables (the variables need to be coded in such a way that data.matrix converts them to something numeric). If xvarsorted=TRUE, a single integer, number of categorical variables.

Value

A list with components

data

data matrix with continuous variables first and categorical variables in standard coding behind them.

ppdim

vector of categorical variable-wise numbers of categories.

discretelevels

list of levels of the categorical variables belonging to what is treated by flexmixedruns as category 1, 2, 3 etc.

continuous

number of continuous variables.

discrete

number of categorical variables.

Author(s)

See Also

Examples

set.seed(776655)
  v1 <- rnorm(20)
  v2 <- rnorm(20)
  d1 <- sample(c(2,4,6,8),20,replace=TRUE)
  d2 <- sample(1:4,20,replace=TRUE)
  ldata <- cbind(v1,d1,v2,d2)
  lc <-
  discrete.recode(ldata,xvarsorted=FALSE,continuous=c(1,3),discrete=c(2,4))
  require(MASS)
  data(Cars93)
  Cars934 <- Cars93[,c(3,5,8,10)]
  cc <- discrete.recode(Cars934,xvarsorted=FALSE,continuous=c(2,3),discrete=c(1,4))

fpc

Flexible Procedures for Clustering

v2.2-9
GPL
Authors
Christian Hennig <christian.hennig@unibo.it>
Initial release
2020-12-06

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