`X`

and updated `pars`

and
`randPars`

to include any dummy-coded categorical or interaction
variables.`R/encoding.R`

`recodeData.Rd`

Recodes the data and returns a list of the encoded design matrix (`X`

) as
well as two vectors (`pars`

and `randPars`

) with discrete (categorical)
variables and interaction variables added to `X`

, `pars`

, and
`randPars`

.

`recodeData(data, pars, randPars)`

- data
The data, formatted as a

`data.frame`

object.- pars
The names of the parameters to be estimated in the model. Must be the same as the column names in the

`data`

argument. For WTP space models, do not include price in`pars`

- it should instead be defined by the`scalePar`

argument.- randPars
A named vector whose names are the random parameters and values the distribution:

`'n'`

for normal or`'ln'`

for log-normal. Defaults to`NULL`

.

A list of the design matrix (`X`

) and two vectors (`pars`

and
`randPars`

) with discrete (categorical) variables and interaction variables
added.

```
library(logitr)
data(yogurt)
# Recode the yogurt data
result <- recodeData(
data = yogurt,
pars = c("price", "feat", "brand", "price*brand"),
randPars = c(feat = "n", brand = "n")
)
result$formula
#> ~price + feat + brand + price * brand
#> <environment: 0x7fad67b8d4d8>
result$pars
#> [1] "price" "feat" "brandhiland"
#> [4] "brandweight" "brandyoplait" "price:brandhiland"
#> [7] "price:brandweight" "price:brandyoplait"
result$randPars
#> feat brandhiland brandweight brandyoplait
#> "n" "n" "n" "n"
head(result$X)
#> price feat brandhiland brandweight brandyoplait price:brandhiland
#> 1 8.1 0 0 0 0 0.0
#> 2 6.1 0 1 0 0 6.1
#> 3 7.9 0 0 1 0 0.0
#> 4 10.8 0 0 0 1 0.0
#> 5 9.8 0 0 0 0 0.0
#> 6 6.4 0 1 0 0 6.4
#> price:brandweight price:brandyoplait
#> 1 0.0 0.0
#> 2 0.0 0.0
#> 3 7.9 0.0
#> 4 0.0 10.8
#> 5 0.0 0.0
#> 6 0.0 0.0
```