[R] remove outlier

[David Winsemius]

On Jan 2, 2015, at 4:58 AM, Methekar, Pushpa (GE Transportation, Non-GE) wrote:

> Hi ,
> I am working on a function .
> 
> rm.outliers = function(dataset,model){
>     dataset$predicted = predict(model)
>    dataset$stdres = rstudent(model)
>     m = 1
>     for(i in 1:length(dataset$stdres)){
>       dataset$outlier_counter[i] = if(dataset$stdres[i] >= 3 |
>                                             dataset$stdres[i] <= -3) {m}
>                                     else{0}
>      }
>   j = length(which(dataset$outlier_counter >= 1))
>    while(j>=1){
>       print(dataset[which(dataset$outlier_counter >= 1),])
>        dataset = dataset[which(dataset$outlier_counter == 0),]
>        dataset$predicted = predict(model)
>      dataset$stdres = rstudent(model)
>          m = m+1
>          for(k in 1:length(dataset$stdres)){
>              dataset$outlier_counter[k] = if(dataset$stdres[k] >= 3 |
>                                                    dataset$stdres[k] <= -3) {m} else{0}
>           }
>       j = length(which(dataset$outlier_counter >= 1))
>     }
>   return(dataset)
>  }
> When I pass
> rm.outliers(xsys,fitted.modely1.temp.l)
> fitted.modely1 .temp.l  is mylinear model.
> It shows me error like
> 
> Error in `$<-.data.frame`(`*tmp*`, "predicted", value = c(0.306726561735386,  :
> 
>  replacement has 731 rows, data has 717

When you get a mismatch of "data" and replacement lengths like that it suggests you have NA values in some of the model variables. If that's the case then the absence of an example means we are not be able to demonstrate that effect, but you should be able to make a more modest example and test that hypothesis.

> 
> Called from: `$<-`(`*tmp*`, "predicted", value = c(0.306726561735386, 0.306726561)
> 
> 
> 
> Help me out
> 
> 
> Xsys data has 331 rows and 18 column
> 
> 	[[alternative HTML version deleted]]
> 

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-- 
David.
> 
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David Winsemius
Alameda, CA, USA