superimpose graphs

x <- read.table(textConnection("        id     invest     payout

closeAllConnections()
# normalize 'invest' by the mean
x$investNorm <- ave(x$invest, x$id, FUN = function(a) a / mean(a))
x

# plot the points
plot(x$payout, x$investNorm)

Hi there,

I have a data frame DF of over 600 people's short term trade data in time
order. Below is the simplified structure of the data.

? ? ? ? id ? ? invest ? ? payout
[1] ? ? ?1 ?10 ? ? ? ? ? ? ? -1
[2] ? ? ?1 ? ? ? ? ?33 ? ? ? ? ? 33
[3] ? ? ?1 ?20 ? ? ? ? ? ? ? -5
[4] ? ? ?2 ? ? ? ? ?200 ? ? ? ? ?33
[5] ? ? ?2 ? ? ? ? ?33 ? ? ? ?-20
[6] ? ? ?3 ? ? ? ? ? 5 ? ? ? ? ?-5
[7] ? ? ?3 ?5 ? ? ? ?-5

id is each person's id. Each person have invested many times in the sampling
period, in temporal order.

What I want to check is the correlation between invest and payout.

1. How do I run the regression for each person, with the "invest" being
devided by the mean or medium of the person's "invest"?
2. How do I plot a graph with y axis being invest/mean(invest) and x axis
being payout, all 600 people's dots superimposed on one graph?

I tried to use

for (i in 1:(dim (DF)[1]-1))
?{
if (DF[i,1]=DF[i+1,1]) ? id.lm <- lm(invest ~ payput, data=DF)
}

But I don't know how to superimpose graphs onto each other.

Thanks a lot!

Su

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