Hi Anthony,
No, I don't believe this exists on CRAN already (happy to be proven
wrong though) but I might suggest you approach things a different way:
instead of defining this operator by operator with infix notation, why
not go after `+`, `>` directly? If you put a class on your vectors,
you can define Ops.class which will change the behavior of all those
sorts of things.
Simple example (probably not complete nor necessarily advisable)
a <- c( 1 , NA , 7 , 2 , NA )
b <- c( NA , NA , 9 , 1 , 6 )
class(a) <- class(b) <- "damico"
Ops.damico <- function(e1, e2 = NULL){
e1[is.na(e1)] <- 0
e2[is.na(e2)] <- 0
NextMethod()
}
a < b
More nuance is available, but this hopefully gives you a start. You
might, e.g., think about setting this as something more like:
Ops.damico <- function(e1, e2 = NULL){
if(.Generic %in% c("==","!=","<","<=",">=",">")){
e1[is.na(e1)] <- 0
e2[is.na(e2)] <- 0
}
NextMethod()
}
so you don't mess up arithmetic but only the boolean comparisons.
Best,
Michael
On Wed, Jun 20, 2012 at 3:44 PM, Anthony Damico <ajdam...@gmail.com> wrote:
> Hi, I work with data sets with lots of missing values. We often need
> to conduct logical tests on numeric vectors containing missing values.
> I've searched around for material and conversations on this topic,
> but I'm having a hard time finding anything. Has anyone written a
> package that deals with this sort of thing? All I want are a group of
> functions like the ones I've posted below, but I'm worried I'm
> re-inventing the wheel.. If they're not already on CRAN, I feel like
> I should add them. Any pointers to work already completed on this
> subject would be appreciated. Thanks!
>
> Anthony Damico
> Kaiser Family Foundation
>
>
>
> Here's a simple example of what I need done on a regular basis:
>
> #two numeric vectors
> a <- c( 1 , NA , 7 , 2 , NA )
>
> b <- c( NA , NA , 9 , 1 , 6 )
>
> #this has lots of NAs
> a > b
>
> #save this result in x
> x <- (a > b)
>
> #overwrite NAs in x with falses (which we do a lot)
> x <- ifelse( is.na( x ) , F , x )
>
> #now x has only trues and falses
> x
>
>
>
> ################
> Here's an example function that solves the problem for "greater than"
> ################
>
>
> #construct a function that performs the same steps:
> "%>F%" <-
> function( a , b ){
>
> x <- (a > b)
>
> x.false <- ifelse( is.na( x ) , F , x )
>
> x.false
>
> }
>
> #run the function
>
> a %>F% b
>
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