R: Recodes mixed variables dataset

discrete.recode {fpc} | R Documentation

## 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)

Christian Hennig c.hennig@ucl.ac.uk http://www.homepages.ucl.ac.uk/~ucakche

### See Also

`lcmixed`

### 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))

[Package fpc version 2.1-10 Index]