Here is the solution using pmin/pmax for 10,000 rows.
> min_pctle_cut <- 0.01
> max_pctle_cut <- 0.99
> library(outliers)
>
> n <- 1
> x1 <- runif(n)
> x2 <- runif(n)
> x3 <- x1 + x2 + runif(n)/10
> x4 <- x1 + x2 + x3 + runif(n)/10
> x5 <- factor(sample(c('a','b','c'),n,replace=TRUE))
> x6 <-
You can easily vectorize this code using pmin/pmax.
Sent from my iPad
On Nov 22, 2011, at 1:06, Aher wrote:
> Hi Experts,
>
> I am new to R, using following sample code for capping outliers using
> percentile information. Working on large data (3 observations and 150
> variables), loop I
Hi Experts,
I am new to R, using following sample code for capping outliers using
percentile information. Working on large data (3 observations and 150
variables), loop I am using in the below mentioned code for detecting
outliers and capping to upper /lower percentile value is taking much ti
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