| impute_lr {deductive} | R Documentation |
Impute values derived from linear (in)equality restrictions.
Description
Partially filled records \boldsymbol{x} under linear (in)equality
restrictions may reveal unique imputation solutions when the system
of linear inequalities is reduced by substituting observed values.
This function applies a number of fast heuristic methods before
deriving all variable ranges and unique values using Fourier-Motzkin
elimination.
Usage
impute_lr(dat, x, ...)
## S4 method for signature 'data.frame,validator'
impute_lr(dat, x, methods = c("zeros", "piv", "implied"), ...)
Arguments
dat |
an R object carrying data |
x |
an R object carrying validation rules |
... |
arguments to be passed to other methods. |
methods |
What methods to use. Add 'fm' to also compute variable ranges using fourier-motzkin elimination (can be slow and may use a lot of memory). |
Note
The Fourier-Motzkin elimination method can use large amounts of memory and may be slow. When memory allocation fails for a ceratian record, the method is skipped for that record with a message. This means that there may be unique values to be derived but it is too computationally costly on the current hardware.
Examples
v <- validate::validator(y ==2,y + z ==3, x +y <= 0)
dat <- data.frame(x=NA_real_,y=NA_real_,z=NA_real_)
impute_lr(dat,v)