Hi Cristian,
yes, indeed. What I'm not sure about is how doing this by groups will
give you a different result, if the object is already sorted according
to the group structure. As you are working with differences, each
group 'loses' an observation, which will be the observation that is
calculat
Thanks Andrew, but what you gave me can actually be done simpler like
my_agg$vol.diff <- diff(my_agg$Vol)
or
my_agg$vol.diff <-c(NA, diff(my_agg$Vol)) # for a list with the same
#length as the aggregated mean list
However, what I need is to be able to h
Hi Cristian,
instead of aggregate, how about something like:
n <- dim(my_agg)[1]
my_agg$vol.diff <- my_agg$Vol - c(NA, my_agg$Vol[1:(n-1)]
my_agg <- my.agg[my.agg$Age > min(my.agg$Age),]
(assumes same minimum age for all treatments)
(not checked)
Cheers,
Andrew
On Thu, Nov 01, 2007 at 12:0
Hi everyone
I am trying to summarize a table with yield estimates of a forest
plantation. For that I have four blocks and four treatments measured over
a period of 10 years (every year). In each plot trees are measured
(diameters and heights).
With aggregate function I can calculate the average
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