outliers

Given an array like [15, 14, 12, 3, 10, 4, 2, 1] . How can I determine which elements are out of order and remove them (the number 3 in this case). I don't want to sort the list, but detect outliers and remove them. Another example: [13, 12, 4, 9, 8, 6, 7, 3, 2] I want to be able to remove #4 and #7 so that I end up with: [13, 12, 9, 8, 6, 3, 2] There's also a problem that arises when you have this scenario: [15, 13, 12, 7, 10, 5, 4, 3] You could either remove 7 or 10 to make this array sorted. In general, the problem I'm trying to solve, is that given a list of numerical readings (some could

I am a R-novice. I want to do some outlier cleaning and over-all-scaling from 0 to 1 before putting the sample into a random forest. g<-c(1000,60,50,60,50,40,50,60,70,60,40,70,50,60,50,70,10) If i do a simple scaling from 0 - 1 the result would be: > round((g - min(g))/abs(max(g) - min(g)),1) [1] 1.0 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.1 0.1 0.0 0.1 0.0 0.1 0.0 0.1 0.0 So my idea is to replace the values of each column that are greater than the 0.95-quantile with the next value smaller than the 0.95-quantile - and the same for the 0.05-quantile. So the pre-scaled result would be: g<-c(**70**,60,50

I have the following data set that I am trying to plot with ggplot2, it is a time series of three experiments A1, B1 and C1 and each experiment had three replicates. I am trying to add a stat which detects and removes outliers before returning a smoother (mean and variance?). I have written my own outlier function (not shown) but I expect there is already a function to do this, I just have not found it. I've looked at stat_sum_df("median_hilow", geom = "smooth") from some examples in the ggplot2 book, but I didn't understand the help doc from Hmisc to see if it removes outliers or not. Is

I would like to plot each column of a matrix as a boxplot and then label the outliers in each boxplot as the row name they belong to in the matrix. To use an example: vv=matrix(c(1,2,3,4,8,15,30),nrow=7,ncol=4,byrow=F) rownames(vv)=c("one","two","three","four","five","six","seven") boxplot(vv) I would like to label the outlier in each plot (in this case 30) as the row name it belongs to, so in this case 30 belongs to row 7. Is there an easy way to do this? I have seen similar questions to this asked but none seemed to have worked the way I want it to. 42- In the example given it's a bit boring

I'd like to replace all values in my relatively large R dataset which take values above the 95th and below the 5th percentile, with those percentile values respectively. My aim is to avoid simply cropping these outliers from the data entirely. Any advice would be much appreciated, I can't find any information on how to do this anywhere else. This would do it. fun <- function(x){ quantiles <- quantile( x, c(.05, .95 ) ) x[ x < quantiles[1] ] <- quantiles[1] x[ x > quantiles[2] ] <- quantiles[2] x } fun( yourdata ) You can do it in one line of code using squish() : d2 <- squish(d, quantile(d, c(