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Hi,
I think NA in data is the most common case in practice, and I don't known how to specify na.rm=T or na.rm=F in some NA sensitive functions like mean sum?
Xie Kun.
The text was updated successfully, but these errors were encountered:
Thanks for your interest in the package, and you're absolutely right, NA is ubiquitous in data!
With the way winScan() works at the moment, you have two options: 1) remove the missing values before doing the window summaries or 2) create a custom function to pass to winScan().
I will exemplify both with some simple example data:
library(WindowScanR) # load the library# Create some example data with missing valuesdf<-data.frame(x=1:10, y= c(1, 1, 2, NA, 3, 3, NA, 3, 2, 2))
This is what it looks like:
x y
1 1
2 1
3 2
4 NA
5 3
6 3
7 NA
8 3
9 2
10 2
Option 1
Remove missing values before doing the window summaries. For example:
Hi,
I think NA in data is the most common case in practice, and I don't known how to specify na.rm=T or na.rm=F in some NA sensitive functions like mean sum?
Xie Kun.
The text was updated successfully, but these errors were encountered: