One of the components which can be added to a `sim_setup`

. These functions can be used for adding new variables to the data.

1 2 3 4 5 | ```
sim_comp_pop(simSetup, fun = comp_var(), by = "")
sim_comp_sample(simSetup, fun = comp_var(), by = "")
sim_comp_agg(simSetup, fun = comp_var(), by = "")
``` |

`simSetup` |
a |

`fun` |
a function, see details. |

`by` |
names of variables as character; identifying groups for which fun is applied. |

Potentially you can define a function for computation yourself. Take care that it only has one argument, named `dat`

, and returns a `data.frame`

. Use `comp_var`

for simple data manipulation. Functions added with `sim_comp_pop`

are applied before sampling; `sim_comp_sample`

after sampling. Functions added with `sim_comp_agg`

after aggregation.

`comp_var`

, `sim_gen`

, `sim_agg`

, `sim_sample`

, `sim_comp_N`

, `sim_comp_n`

, `sim_comp_popMean`

, `sim_comp_popVar`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
# Standard behavior
sim_base() %>% sim_gen_x() %>% sim_comp_N()
# Custom data modifications
## Add predicted values of a linear model
library(saeSim)
comp_lm <- function(dat) {
dat$linearPredictor <- predict(lm(y ~ x, data = dat))
dat
}
sim_base_lm() %>% sim_comp_pop(comp_lm)
# or if applied after sampling
sim_base_lm() %>% sim_sample() %>% sim_comp_pop(comp_lm)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.