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 there a function to remove outliers like this in ggplot, or where would I amend my code below to add my own function?

library (ggplot2)  

data = data.frame (day = c(1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7), od = 
c(
0.1,1.0,0.5,0.7
,0.13,0.33,0.54,0.76
,0.1,0.35,0.54,0.73
,1.3,1.5,1.75,1.7
,1.3,1.3,1.0,1.6
,1.7,1.6,1.75,1.7
,2.1,2.3,2.5,2.7
,2.5,2.6,2.6,2.8
,2.3,2.5,2.8,3.8), 
series_id = c(
"A1", "A1", "A1","A1",
"A1", "A1", "A1","A1",
"A1", "A1", "A1","A1",
"B1", "B1","B1", "B1",
"B1", "B1","B1", "B1",
"B1", "B1","B1", "B1",
"C1","C1", "C1", "C1",
"C1","C1", "C1", "C1",
"C1","C1", "C1", "C1"),
replicate = c(
"A1.1","A1.1","A1.1","A1.1",
"A1.2","A1.2","A1.2","A1.2",
"A1.3","A1.3","A1.3","A1.3",
"B1.1","B1.1","B1.1","B1.1",
"B1.2","B1.2","B1.2","B1.2",
"B1.3","B1.3","B1.3","B1.3",
"C1.1","C1.1","C1.1","C1.1",
"C1.2","C1.2","C1.2","C1.2",
"C1.3","C1.3","C1.3","C1.3"))

> data
   day   od series_id replicate
1    1 0.10        A1      A1.1
2    3 1.00        A1      A1.1
3    5 0.50        A1      A1.1
4    7 0.70        A1      A1.1
5    1 0.13        A1      A1.2
6    3 0.33        A1      A1.2
7    5 0.54        A1      A1.2
8    7 0.76        A1      A1.2
9    1 0.10        A1      A1.3
10   3 0.35        A1      A1.3
11   5 0.54        A1      A1.3
12   7 0.73        A1      A1.3
13   1 1.30        B1      B1.1

This is what I have so far and is working nicely, but outliers are not removed:

r <- ggplot(data = data, aes(x = day, y = od))
r + geom_point(aes(group = replicate, color = series_id)) + # add points
   geom_line(aes(group = replicate, color = series_id)) + # add lines
   geom_smooth(aes(group = series_id))  # add smoother, average of each replicate