Hi Rebecca,
I think it was me how suggested you the missRanger package, so this is
actually a follow-up of you previous question about censored imputation
of missing values (as far as I can remember).
The missRanger package uses predictive mean matching, so take a look at
?missRanger::pmm and in general read a bit about what 'predictive mean
matching' means.
In a nutshell: If your data is appropriate for this technique, you do
not need to take care of explicit censoring - it will be done implicitly
by the package.
Cheers,
Denes
On 11/12/2018 09:12 PM, Bert Gunter wrote:
You have asked what I believe is an incoherent question, and thus are
unlikely to receive any useful replies (of course, I may be wrong about
this...).
Please read and follow the posting guide linked below to to ask a question
that can be answered.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Nov 12, 2018 at 12:03 PM Rebecca Bingert <rebecca.bing...@gmx.de>
wrote:
Hi,
does anybody know where I need to insert the censoring in the missRanger
package?
Regards,
Rebecca
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