The problem is the representation.
If we transform it into a zoo time series, z, with one
series per column and one time point per row then we
can just merge the series with its lag.
DF - data.frame(id = c(1, 1, 1, 2, 2, 2), time = c(1, 2,
+ 3, 1, 2, 3), value = c(-0.56047565, -0.23017749, 1.55870831,
+ 0.07050839, 0.12928774, 1.71506499))
library(zoo)
z - do.call(merge, by(DF, DF$id, function(x) zoo(x$value, x$time)))
merge(z, lag(z, -1))
1.z2.z 1.lag(z, -1) 2.lag(z, -1)
1 -0.5604756 0.07050839 NA NA
2 -0.2301775 0.12928774 -0.5604756 0.07050839
3 1.5587083 1.71506499 -0.2301775 0.12928774
On Dec 13, 2007 1:21 PM, Antonio, Fabio Di Narzo
[EMAIL PROTECTED] wrote:
Hi all.
I'm looking for robust ways of building lagged variables in a dataset
with multiple individuals.
Consider a dataset with variables like the following:
##
set.seed(123)
d - data.frame(id = rep(1:2, each=3), time=rep(1:3, 2), value=rnorm(6))
##
d
id time value
1 11 -0.56047565
2 12 -0.23017749
3 13 1.55870831
4 21 0.07050839
5 22 0.12928774
6 23 1.71506499
I want to compute the lagged variable 'value(t-1)', taking subject id
into account.
My current effort produced the following:
##
my_lag - function(dt, varname, timevarname='time', lag=1) {
vname - paste(varname, if(lag0) '.' else '', lag, sep='')
timevar - dt[[timevarname]]
dt[[vname]] - dt[[varname]][match(timevar, timevar + lag)]
dt
}
lag_by - function(dt, idvarname='id', ...)
do.call(rbind, by(dt, dt[[idvarname]], my_lag, ...))
##
With the previous data I get:
lag_by(d, varname='value')
id time value value.1
1.1 11 -0.56047565 NA
1.2 12 -0.23017749 -0.56047565
1.3 13 1.55870831 -0.23017749
2.4 21 0.07050839 NA
2.5 22 0.12928774 0.07050839
2.6 23 1.71506499 0.12928774
So that seems working. However, I was thinking if there is a
smarter/cleaner/more robust way to do the job. For instance, with the
above function I get dataframe rows re-ordering as a side-effect
(anyway this is of no concern in my current analysis)...
Any suggestion?
All the bests,
Fabio.
--
Antonio, Fabio Di Narzo
Ph.D. student at
Department of Statistical Sciences
University of Bologna, Italy
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