# impestcond: Conditional Imprecise Estimation In impimp: Imprecise Imputation for Statistical Matching

## Description

Estimate conditional probability of some events based on data obtained by imprecise imputation

## Usage

 `1` ```impestcond(data, event, condition, constraints = NULL) ```

## Arguments

 `data` a data.frame obtained as result from an imprecise imputation e.g. by a call to `impimp`. `event` a list of objects of class `"impimp_event"`, specifiying the event of interest. See 'Details'. `condition` a list of objects of class `"impimp_event"`, specifiying the event to condition on. See 'Details'. `constraints` a list of so-called logical constraints or fixed zeros. Each element must be an object of class `"impimp_event"`. See 'Details' .

## Details

`event` and `condition` should each be a list of objects of class `"impmp_event"`, where within each list the set union of impimp_events is the actual event of interest or conditioning event, respectively.

By specifying `constraints` one can exlude combinations of imputed values which are deemed impossible, so called ‘logical constraints’ or ‘fixed zeros’. `constraints` should be a list of objects of class `"impimp_event"`.

An object of class `"impimp_event"` is obtained as a result of a call to `impimp_event`.

For `event`, `condition` and `constraints` holds that overlapping in the resulting events generated by the individual impimp_events does not have any side effects, besides a potential decrease in performance.

## Value

A numeric vector of length 2, where the first component contains the lower and the second component the upper conditional probability of the event of interest.

## References

Dubois, D. and Prade, H. (1992), Evidence, knowledge, and belief functions, International Journal of Approximate Reasoning 6(3), 295–319.

## See Also

`impimp`, `impimp_event` for sepcifying constraints and events; `impest` for the estimation of unconditional probabilities

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17``` ```A <- data.frame(x1 = c(1,0), x2 = c(0,0), y1 = c(1,0), y2 = c(2,2)) B <- data.frame(x1 = c(1,1,0), x2 = c(0,0,0), z1 = c(0,1,1), z2 = c(0,1,2)) AimpB <- impimp(A, B, method = "domain") BimpA <- impimp(B, A, method = "domain") AB <- rbindimpimp(AimpB, BimpA) myevent <- list(impimp_event(z1 = 1,z2 = 0), impimp_event(z1 = c(0,1), z2 = 1)) cond <- list(impimp_event(x1 = 1)) impestcond(AB, event = myevent, condition = cond) constr <- list(impimp_event(y1 = 0, z1 = 0)) impestcond(AB, event = myevent, condition = cond, constraints = constr) ```

impimp documentation built on May 1, 2019, 10:13 p.m.