Q:

how to identify outliers in a scatterplot matrix made using splom?

I have data on weather variables such as temperature, rainfall etc for the period 2001-2009 for various locations in India. 
To see the relationship between these variables, I create a scatterplot matrix using splom with the following code.
   library(lattice)
   library(RColorBrewer)
   splom(~aod_corr[c(5,8,11,14)], lower.panel = panel.splom,
  upper.panel = function(x, y, ...) {
      panel.fill(col = brewer.pal(9, "RdBu")[ round(cor(x, y) * 4 + 5)])
      panel.text(mean(x), mean(y), round(cor(x, y),2), font=2)
  },

 scales = list(x = list( draw = TRUE, cex=0.1)), type = c("g", "p", "smooth"),layout =     c(1, 1))

I now wish to identify the outliers in each panel that I can trace back to the data. How can I do so?

A:

Seems like this is a job for the function panel.link.splom. See here
http://procomun.wordpress.com/2011/03/18/splomr/

A:

Based on the link given by @Karsten I give you  a sceanrio of interaction with splom object:

I plot my splom
I identify the panel
I choose some points using link splom
I escape to get the results

details:

I create a splom using lattice splom
Interaction:
## I get the focus on the major panel (red color)
trellis.focus('panel', 1, 1)
## I link my panel to the splom
idx <- panel.link.splom(pch=13, cex=0.6, col='green')

I choose some points with the mouse. They will colored in green
Escape to get the focus
Check the result
str(idx)   num [1:5] 111 95 132 96 15

